Wrong on so many levels: The Amyloid Cascade hypothesis and Alzheimer's disease

Our body, including our brain, is constantly changing. Within each of the 37 trillion cells [1]  there is a constant dynamic activity. A relentlessly hive of activity maintaining, coordinating and enhancing functioning. All of this activity is based on four major molecules—macromolecules—essential for all known forms of life. These are fats, carbohydrates, nucleic acids and proteins. 

Fats and carbohydrates are the source of all energy for the body, while nucleic acids (meaning from the nucleus) and proteins (meaning primary or first) constitute the components of the body.

Nucleic acids hold our genetic material our DNA—Deoxyribonucleic Acid—whose sole purpose is to make and coordinate the production of proteins. DNA is stored in the nucleus while a replica of this DNA called RNA—Ribonucleic Acid—is a working copy of the many parts—called genes—of the DNA. The sole purpose of the DNA and RNA is to hold information that make up all the proteins that our body needs.

RNAs are thought to be earlier versions of DNA, our genetic templates. At some point the strand of information that contains the four nucleotides—chemical codes—must have combined with another RNA strand to form a DNA helix, a more stable and accurate structure. This structure is more stable because each nucleotide, piece of information, is matched on the other side of the double helix—like double entry book keeping, resulting in less chance of making mistakes. This robustness is a necessary feature if you aim to become immortal, as genes are.

Because the DNA is a stable structure, it must however be unwound and transcribed to form copies of RNAs which can then be translated to proteins. Proteins—which are made up of amino acids—function as enzymes, hormones and body tissues. The importance of proteins is expressed by the recent ambition to map all human proteins in the Human Proteome Project. Just because we mapped the genome does not mean very much if you do not know what those codes mean. Proteins are the deciphering tool.

As there are more proteins than genes, the aim to map all proteins is ambitious and much larger than mapping the genome. It is also very complex. The proteome has two additional levels of complexity. While the genome is defined by the sequence of four nucleotides, the proteome is determined by the same genome but then involving the permutations of 20 different amino acids. Each amino acid is defined by a set of three nucleotides on the RNA—a codon. A chain of amino acid is defined as a protein, having varying sequence and lengths. Each variation defines the physical structure, and the structure determines its function. This complexity resides within nearly each of our 37 trillion cells. Cells within specific organs produce specific proteins, although all cells have the capacity to synthesize all proteins.

In our body, most of our cells have a nucleus and a membrane around it—Eukaryotic Cell as apposed to Prokaryotic Cell. Within these eukaryotic cells is a complex factory of activity. Not only have eukaryotic cells evolved to include alien small organs— organelle such as mitochondria which have their own genetic material separate from the cell’s DNA—each cell has a copy of all of our genetic material, our body’s complete template.  How our genes virtually replace or maintain each and every cell as we live, is one of the most intriguing enigmas in science.

The DNA is like a musical record that is being played constantly. Instead of sound, the player—an enzyme, another protein, called ribozyme—makes negative copies of one strand of the DNA. Through a process known as transcription—it produces a negative copy called the RNA. As the DNA is transcribed, a strand of RNA is created within the nucleus of the cell. This RNA strand migrates out of the nucleus wall into the cytoplasm, the main part of the cell. This small negative replica is composed of a string of nucleotides which are “read” three nucleotides at a time—these keys are called codons. To produce protein, the DNA transcribes three types of RNA.

One part defines the type of protein to build, this is the messenger RNA—mRNA. The second RNA strand is a transfer RNA—tRNA—which attaches to a specific amino acid. Like a shopping trolley, it selects individual amino acids as the building blocks of protein. The final structure —rRNA—is the two-part machine called a ribosome, that builds the protein itself. Ribosomes combine the messenger and the transfer RNA according to the code, the codon. As it matches them together it then steals their amino acids. Ribosomes join one amino acid with the subsequent amino acid, creating chains of amino acids. This is the birth of a protein.

A protein starts life in the cell as a long chain of, on average, 300 of these amino acids. There are 20 different types of amino acids—nine are called essential that we need to get from our diet and cannot be manufactured. The sequence and number of amino acids determines how the protein chain will fold upon itself once completed. Some proteins provide structure, others transport molecules, while others help cells to divide and grow. The function of a protein is dependent on their folding structure. It is an origami dictated by the sequences of amino acids and the length of the chain.[2]

Back to Alzheimer’s disease

The Amyloid Cascade hypothesis was first articulated in 1992 [3] and became enshrined in the guidelines published by the National Institute on Aging and Alzheimer’s Association (Jack et al., 2011).  The amyloid cascade hypothesis posits that the deposition of the amyloid-β peptide in the brain is a crucial step that ultimately leads to Alzheimer's disease. Amyloid-β peptide is a small protein called a beta (β) that has misfolded and became an amyloid. [4] Amyloid refers to how small proteins interact together by combining and forming a solid insoluble mass—they become hydrophobic, shy of water, because of how they fold. This type of interaction has its own designation as a disease called amyloidosis. These misfolded proteins combine together to create plaques of a million or so amyloid beta molecules. According to the National Institute on Aging and Alzheimer’s Association, these amyloid beta molecules grow until they interfere with the normal functioning of the brain. This is the cause of Alzheimer’s disease. And they have tested and substantiated this theory with mice models. But there is a problem.

The problem

The Amyloid Cascade hypothesis has not been supported by the data on humans. To date most of the treatments tested in human clinical trials are amyloid-β-based drugs, including those that remove amyloid-β. Despite the success of these drugs in removing the plaques from the brains of Alzheimer’s disease patients, the effect on behavior and thinking was negative.  [5]    Patients who had the misfolded proteins removes chemically did worse in tests than before the intervention. [6]

It seems that the clinical expression, the behavior, is not solely determined by increases in misfolded protein. A longitudinal study reported that eight percent of participants who behaved and acted free from dementia—when they died and had their brain examined—were found to have the most severe neuropathology. [7]  Despite having abundant and severe disease—neurofibrillary tangles and senile plaques—they had normal functioning.

Approximately half of clinically demented oldest-old have insufficient neuropathology to account for their dementia. [8]  While approximately thirty to fifty percent of older adults without dementia meet the neuropathological criteria for Alzheimer’s disease. [9]

The reality

The story of errors in making proteins which end up in the brain, as the cause of neurological disease, is incomplete. The repetitive story about the biology is also intentionally simplistic. In reality, science is still too naïve to understand the molecular biology of cells and therefore the biology of Alzheimer’s disease. Although geneticists play with genes and create amazing results, we still do not understand the fundamental nature of biology. And we cannot understand the biology of Alzheimer’s disease before we can understand the molecular biology of cells.

Scientists make simplified determination despite knowing only a very small proportion of the biology of cell functioning. We might have traced most of the dance moves, but we still do not know the music. That symphony that all our cells are all dancing to remains mute. With a complex choreography of steps there remains new ones to identify. We are missing the poetry because of the words, and we are missing the music because of the steps.

Each DNA sequence that contains instructions to make proteins is known as a gene. There are two variants of the same type of gene called alleles. Consider these as the paired dancers, with one being “dominant” over the other. There might be many (more than two) alleles for the same gene. How alleles communicate each other’s protein is unknown, especially how they communicate with alleles from a different gene. Unless we know the music of the dance, all that we can see is that there is communication and we can predict the outcome using a mathematical model. [10] However, prediction does not mean that we understand the mechanism.  

Another perplexity is that the size of a gene may vary greatly, ranging from about 1,000 individual nucleotides (bases) to 1 million bases. Genes that make protein—defined by unique start and stop codons—only make up about 1 percent of the DNA sequence. The rest is—we think—involved in the regulation. Around 99 percent of all genetic material is devoted to coordination.

Coordination of protein production—-how and how much of a protein is made; distribution, equilibrium and maintenance, including protection from viruses, bacteria, aberrant cells and malformations. This is the dance music and it seems that DNA is more invested in the music than the dance.

Regulation is the music of this dance that we see in protein synthesis. The transcription—DNA to RNA—and translation—RNA to protein synthesis—involves constant feedback, ensuring an equilibrium within the whole body. So far we are still mapping steps in the dance. It is a mystery how DNA self-polices itself, but it does. It edits code and monitors outcomes. [11]  For example in gene splicing, the initial messenger RNA is edited by removing introns--and joining exons together. And it does this as a dance. First it identifies the beginning and the end of the intron by its nucleotides. Small proteins (snRNPs), bind to these ends of the intron and forms a loop. The loop is then removed leaving the two remaining exons to link together. In addition to this method, there are alternate splicing methods which create many different variations from the same gene. In 2000 S. Lawrence Zipursky and his colleagues at the University of California, Los Angeles (UCLA) identified that this alternate splicing resulted in "one gene–many polypeptides." From one template (gene) there are multiple ways of generating different proteins. How this is done is a mystery. But we know it is not a simple mechanistic process. This is a rhapsody that constantly repeats itself 37 trillion times in each of our cells.

And looking at this fathomless universe, you have to wonder, where does this leave the Amyloid Cascade hypothesis? If the music becomes faulty, then the dance becomes erratic. And we can see this not in one or two steps, but in a series of steps across the body. 

Imbalance

Protein mis-folding is continuous and “normal.”  The ribosome which reads the DNA to make the proteins makes mistakes in as many as 1 in every 7 proteins.  The gene splicing seems variable. Proteins can misfold through other mechanisms. For example, one of the amino acid might be deformed and eventually effect the whole protein. Or the protein is formed perfect but the conditions inside the cell—e.g. temperature or acidity—make it fold unconventionally. Sometimes the misfold is a required fold.  Perhaps the gene itself is dictating a misfold. We have to be careful with this concept of misfold and errors. These are moral judgments.  Especially when some combination of misfolded proteins--amyloids--are naturally produced to carry out necessary functions in the body.

Neal Hammer with the University of Michigan Medical school, and his colleagues, [12] reviewed cases where the amyloid has been shown to be a necessary feature. The authors conclude that “Despite over twenty years of [Alzheimer’s disease] AD research the nature of the toxic species of Aβ has yet to be conclusively identified and little is known about how Aβ polypeptide aggregation begins in vivo.“

We still do not know for certainty how many proteins there are in the body. The Human Proteone Project has so far identified 30,057 proteins. [13]  This figure might be revised to 100,000 unique types of proteins in humans. We also do not know the full extent, how often, and the overall consequence of misfolded proteins.  Aβ can be formed from 18 inappropriately folded versions of proteins naturally present in the body. But there are many more misfolded proteins that we have already identified, more remain to be identified. [14]  One thing that we have learned from nature is that errors are the salvation to immortality. Humans are the product of errors and the immortality of genes relies on the continuation of errors. Perhaps we should refrain from judging nature too early in our knowledge.

Amyloidosis in Alzheimer's disease.

The problem, we are told, is that when proteins fold incorrectly some become amyloids. And this happens so frequently that it becomes a disease all by itself called Amyloidosis. This physical expressions of the disease is determined by the type of protein that is misfolded and the organ or tissue it resides in. [15]  By studying amyloidosis it is now believed that certain misfolded small proteins called “seeds” can induce other proteins to fold—known as the study of proteopathy.  This is exactly what happens with the prion misfolded protein which causes a cascade of prion disease— Creutzfeldt–Jakob disease disease in humans. As with music that orchestrates the dance, the wrong tune will cause multiple wrong steps, and they are related to the same sheet of music. So that, as an example, Alzheimer’s disease is related, both clinically and also statistically, with type 2 diabetes, both seen as diseases of amyloidosis.  The other protein implicated in Alzheimer's disease, tau protein, also forms such prion-like misfolds. There is some evidence that misfolded Aβ can induce tau to misfold, although this might be a symbiotic relationship, one promotes the other.

So the question is why—if the National Institute on Aging and Alzheimer’s Association truly believe in the Amyloid Cascade hypothesis—are they not looking at all of these other diseases of amyloidosis together rather than in silos?

And we know the answer to that question already. [16]

The second question that follows is more fundamental. If all these diseases share a common process, if by addressing the known cause of one can we delay or stop the cause of a secondary disease? Perhaps then, a public health approach to Alzheimer’s disease is warranted. [17]

There is a third and more radical question. If these misfolded proteins are in fact there for a reason and not as a result of error, then what are they protecting us from?

Perhaps we do not know the underlying disease of Alzheimer's yet. There is increasing evidence suggesting that the large amyloid plaques are developed to protect. [18] And science is bearing this out. It could be that although the small misfolds are dangerous because they are small enough to interfere with the workings of synapsis—-by clamping together they become too big to interfere with the small synaptic transmissions. They are likely protecting the brain. Like a scab on a wound.

A research cul de sac might remain as long as we remain in our silos of research. We need to venture out and explore. “Man cannot discover new oceans unless he has the courage to lose sight of the shore.”―André Gide. We need such intellectual honesty to understand the complexity of Alzheimer’s disease and to dig ourselves out of this research cul de sac.

Citations

​[1] Bianconi, E., Piovesan, A., Facchin, F., Beraudi, A., Casadei, R., Frabetti, F., ... & Perez-Amodio, S. (2013). An estimation of the number of cells in the human body. Annals of human biology, 40(6), 463-471.

[2] . With two common structures called “alpha helices,” like a slinky and “beta sheets” like folded paper fan–α-helices have 21 amino acids while β-sheets have 30 amino acids. There are many other types of shapes and varying levels of complexity of the final structure.

[3] Hardy, J. A. & Higgins, G. A. Alzheimer's disease: the amyloid cascade hypothesis. Science 256, 184–185 (1992).

[4] Peptides are small proteins consisting of 2 or more amino acids. Oligopeptides have 10 or fewer amino acids. Polypeptides are chains of 10 or more amino acids, while polypeptides having more than 50 amino acids are classified as proteins.

[5] Iqbal K., Liu, F. & Gong, C.X. (2014). Alzheimer disease therapeutics: focus on the disease and not just plaques and tangles. Biochemical pharmacology, 88(4): 631-639.

[6] Boche D., Donald J., Love S., Harris S., Neal J.W., Holmes C., et al. (2010). Reduction of aggregated tau in neuronal processes but not in the cell bodies after Abeta42 immunisation in Alzheimer’s disease. Acta Neuropathol, 120: 13–20.

Gilman S., Koller M., Black R.S., Jenkins L., Griffith S.G., Fox N.C, et al. (2005). Clinical effects of Abeta immunization (AN1792) in patients with AD in an interrupted trial. Neurology, 64:1553–62.

[7] as defined by Braak & Braak stages:

Snowdon D. (1997). Aging and Alzheimer's Disease: Lessons From the Nun Study. The Gerontologist, 37(2):150-156

Snowdon D.A. (2003).Healthy aging and dementia: findings from the Nun Study. Annals of Internal Medicine, 139(5,2): 450–454.

Snowdon DA, Greiner LH, Mortimer JA, et al. Brain infarction and the clinical expression of Alzheimer disease. The Nun Study. JAMA. 1997;277:813-817.

[8] (Crystal et al 2000; Polvikoski et al 2001)

[9] (Crystal et al, 1988; Polvikoski et al, 2001; Katzman et al, 1988; Tomlinson, Blessed & Roth 1970; Dickson et al, 1997).

[10] Hardy-Weinberg principle

[11] Some of these are:

Antisense RNA—asRNA, piRNA, micRNA—inhibits translation of mRNA by physically obstructing the translation of some of the nucleoids, germ cell and stem cell development, sperm production, and epigenetic process.
Natural antisense transcripts (NATs) are regulatory RNA involved in interference and inhibit gene expression (RNAi), alternative splicing, genomic imprinting, and X-chromosome inactivation
Long and Short non-coding RNA—ncRNA— perform multiple tasks related non protein transcription for four-fifths of all genome. The FANTOM3 project identified ~35,000 non-coding transcripts from ~10,000 distinct loci.

There are also parasitic RNA that we inherited from other retroviruses (in most cases.) But the most interesting are those RNAs involved in post-transcription. The message within each mRNA is edited—known as gene splicing—by other types of RNA. How they know what to delete and edit is a mystery. There are also some RNA that modifies our DNA replication.  Not just through epigenetic switches—which does not change the DNA—but through modification of our DNA itself.

[12] Hammer, N. D., Wang, X., McGuffie, B. A., & Chapman, M. R. (2008). Amyloids: friend or foe?. Journal of Alzheimer's Disease, 13(4), 407-419.

[13] Kim et al. A draft map of the human proteome. 2014. Nature. 509, 575-581.

[14]  Misfolded proteins:

1.              ABri

2.              ADan

3.              Amyloid A protein

4.              Amyloid β peptide

5.              Apolipoprotein AI

6.              Apolipoprotein AII

7.              Apolipoprotein AIV

8.              Atrial natriuretic factor

9.              Beta-2 microglobulin

10.            Calcitonin

11.            Crystallins

12.            Cystatin C

13.            Fibrinogen

14.            Fused in sarcoma (FUS) protein

15.            Gelsolin

16.            Glial fibrillary acidic protein (GFAP)

17.            Immunoglobulin heavy chains

18.            Islet amyloid polypeptide (IAPP; amylin)

19.            Keratoepithelin

20.            Lysozyme

21.            Medin (lactadherin)

22.            Monoclonal immunoglobulin light chains

23.            Notch3

24.            Prion protein

25.            Prolactin

26.            Proteins with tandem glutamine expansions

27.            rhodopsin

28.            Seipin

29.            Serpins

30.            Superoxide dismutase,

31.            Tau protein

32.            TDP-43

33.            Transthyretin

34.            α-Synuclein

[15] Amyloidosis Disease:

Amyloidosis—systemic
Primary systemic amyloidosis
Ig heavy-chain-associated amyloidosis
Secondary (reactive) systemic amyloidosis
Senile systemic amyloidosis
Hemodialysis-related amyloidosis
Hereditary systemic ApoAI amyloidosis
Hereditary systemic ApoAII amyloidosis
Finnish hereditary amyloidosis
Hereditary lysozyme amyloidosis
Hereditary cystatin C amyloid angiopathy
Amyloidosis—localized
Injection-localized amyloidosis
Hereditary renal amyloidosis
Senile seminal vesicle amyloid
Familial subepithelial corneal amyloidosis
Cataract
Medullary thyroid carcinoma
Neurodegenerative diseases
Alzheimer’s disease
Parkinson’s disease
Lewy-body dementia
Huntington’s disease
Spongiform encephalopathies
Hereditary cerebral hemorrhage with amyloidosis
Amyotrophic lateral sclerosis
Familial British dementia
Familial Danish dementia
Familial amyloidotic polyneuropathy
Frontotemporal dementias
Other diseases
Diabetes mellitus
Atherosclerosis
Sickle cell anemia

[16] Garrett MD (2015) Politics of Anguish: How Alzheimer's disease become the malady of the 21st century. Createspace. USA

[17] Garrett MD, & Valle R (2015) A New Public Health Paradigm for Alzheimer’s Disease Research. SOJ Neurol 2(1), 1-9.

Garrett MD &Valle RJ (2016).A Methodological Critique of The National Institute of Aging and Alzheimer’s Association Guidelines for Alzheimer’s disease, Dementia and Mild Cognitive Impairment. Dementia: The International Journal of Social Research and Practice,15(2) 239–254. DOI: 10.1177/1471301214525166

[18]  D.M. Walsh, I. Klyubin, J.V. Fadeeva, et al.Naturally secreted oligomers of amyloid beta protein potently inhibit hippocampal long-term potentiation in vivo Nature, 416 (2002), pp. 535–539

P.M. Douglas, S. Treusch, H.Y. Ren, et al. Chaperone-dependent amyloid assembly protects cells from prion toxicity. Proc Natl Acad Sci USA, 105 (2008), pp. 7206–7211

© USA Copyrighted 2016 Mario D. Garrett

Complexity Theory and Alzheimer's disease: A Call to Action

The brain of a healthy person is constantly changing. Neurons and glial cells constantly die and get replaced with new cells. More than 30,000 proteins constantly misfold and get degraded, they are cleared from the brain. Constant mini injuries to the brain are accommodated without change in capacity. Where memories are constantly re-imaged and prioritized. Where cognitive functions are shifted from one area of the brain to another. All of these events define the daily functioning of our brain. The question that needs to be asked is why does this ongoing maintenance stops or becomes overwhelmed?

The emerging conclusion—that Alzheimer’s disease is a syndrome—derives from a century of anomalies in research. The National Institute on Aging’s and Alzheimer’s Association  (NIA/AA) new guidelines, based on the Amyloid Cascade hypothesis (Jack et al, 2011) are incomplete. Emerging evidence is elaborating a more complex process. More than one cause, or type of causes, may result in similar or different outcomes. The initial injury might or might not progress.  The neurological disease might or might not affect cognition. The chorus of scientists voicing this approach to Alzheimer’s disease is unremitting. These valid criticisms remain shunned from NIA/AA new research agenda.

So far, after a century of confusion in studying Alzheimer’s disease, it is time to stop repeating the same mistakes in the hope of coming up with new results. We need a new methodology that might provide different results.  This new approach comes from Complexity Theory. Complexity Theory is an open theory—many variables, some known others still unknown influence the outcome. The utility of broadening the theory is to allow for a more inclusive approach that allows diverse literature to be included rather than to remain ignored. A simplified view of the brain states that by looking at individual components you can understand the whole machine--as with the Amyloid Cascade hypothesis (Hardy & Higgins, 1992). Such a mechanistic approach—that harks back to the 14th century—is too limited to explain a behavioral disease such as Alzheimer’s disease.

Such models are useful in generating hypotheses but limited in furthering our understanding of how the brain functions.  Especially because of non-linear effects, a large change might result in a small effect and a small change a large effect. We cannot predict what the effect will be. In strokes for example—where a blockage in the blood vessels destroys an area/s of the brain—we might find a large stroke resulting in little diminished capacity or a small stroke with debilitating results. We cannot predict the outcome with certainty even if we know the area of the trauma. Each stroke is unique, as is Alzheimer’s disease.

Within this theory, systems or units exist, seemingly independent from each other that nevertheless rely on each other, communicating directly within a hierarchy of networks. We know these networks exist because of the presence of hormones, neurotransmitters and cytokines mediated in the body by hundreds of different types of lipids, phospholipids, amino acids, monoamines, proteins, glycoproteins, or gases (Mohamed et al, 2005; Clarke & Sperandio, 2005).  Additionally, the system changes and evolves.

A Complexity Theory would address these variances and how the body maintains these systems in balance—a balance that is unique for each individual. This homoeostasis is based on an internal set of regulators, defined by both past experiences and unique adaptive responses to new stimuli from the environment. The theory would also need to refrain from separating our beliefs, expectations, and behavior from the wider social, political, and cultural systems in which we exist. These units interact within the whole system in (as yet) unknown ways (Doidge, 2015; Merzenich, 2013). In such an open system, both established and new external forces can, and do, impinge on its internal activity. The best example of this is psychosomatic illness where although the disease is caused by the psychology of the person—psychogenic—the physical effects are real (Shorter, 2008).

Because Complexity Theory utilizes input from a variety of disciplines, it is necessarily transdisciplinary (Albrecht et al., 1998). It may help address the philosophical complexity exposed by postmodernist philosophy (Cilliers, 1998; Henrickson & McKelvey, 2002). Complexity theory addresses situations where linear cause and effect do not apply. Examples of such complex theories have been applied to biology, management, computer science, psychology, and other fields. In medicine, Complexity Theory has been applied to immunology (eg. Efroni, Harelb & Cohenb, 2005). Brown & Moon (2002) note that the new public health has “advocated a multi-causal approach that saw infectious and chronic, degenerative disorders as being the result of a complex interaction between biophysical, social or psychological factors.” (pp. 362–363.

The theory’s “complexity” is because it is composed of many parts (sub-units) that interconnect in known and unknown ways (Sussman, 1999) and intricate ways (Moses, 2006), where cause and effect are subtle and change over time (Senge, 2014).

In Alzheimer’s disease research, Complexity Theory might explain why many causes may exist although the disease is expressed uniformly. It might also be that depending on where you are in your lifespan, the disease expresses itself differently, evolving across time (Coveney & Highfield, 1995). Complexity Theory attempt to reconcile the unpredictability of different systems—in this case, areas of the brain interact together in ways as yet unknown—with a sense of underlying order and structure (Levy, 2000). Complexity Theory can be the foundation for understanding all types of Alzheimer’s disease. It can easily be adapted to anomalies in research in a way that makes the theory predict outcomes. At the same time, the theory must be able to explain existing anomalies.

How does a theory of Alzheimer’s disease deal with such confounders? Under Complexity Theory these processes are inclusive, and can be mediated and moderated by other variables. For example, Alzheimer’s disease can be mediated by protecting against injuries (e.g. head injuries, toxicity, radiation). It might also be mediated by maintaining a healthy lifestyle (and the effect this has on supplying the brain with oxygen—cerebral perfusion), or eating a healthy balanced and varied diet that provides all the nutrients and bacterial flora that we require at older ages (Bredesen, 2014). While a century of work has looked at how plasticity, neurogenesis and capacity can delay or protect against Alzheimer’s disease. All these factors—injury, penumbra, perfusion, plasticity—become important processes and sub-units in discussing the etiology of the disease under a Complexity Theory.

But perhaps we are not the first to request this: ”….demonstrate to us in an impressive way how difficult it is to define disease solely with respect to their clinical features, especially in the case of those mental disorders which are caused by an organic disease process. (Alzheimer, 1912, p)  Fox, Freeborough & Rossor (1996) conclude by saying that “…no clear cut distinction exists between senile Alzheimer’s disease and normal aging as far as the clinical and anatomo-pathological elements are concerned” (p. 146). If this is true then we are back to square one with Alzheimer’s disease. It is a disease of old age.

Reference.

Garrett MD (2015). Politics of Anguish: How Alzheimer’s disease become the malady of the 21st century. http://www.amazon.com/Politics-Anguish-Alzheimers-disease-century/dp/1518892930

© USA Copyrighted 2016 Mario D. Garrett

Piaget's Missing Cognitive Stage: Socioemotional Selectivity in Older Adulthood

The Swiss psychologist Jean Piaget is a most prolific renaissance man, publishing in biology, psychology, morality, language and philosophy. His lasting legacy has however been his identification and definition of stages in children’s thinking. Each stage is marked by shifts in our understanding of the world, as though our brain clicks into a different qualitative mode of processing information. We cannot learn a specific concept if our mind has not yet developed the capacity to understand it. A theory "so simple only a genius could have thought of it" according to Albert Einstein. The same concept applies to animals, in that their brain is “intelligent’ enough to represent the world they live in to enable them to survive and prosper. The same constrains exist among humans as they develop. Piaget termed this as Genetic Epistemology; how we learn about our environment.

The stages include sensorimotor (up to age 2) preoperational (2-7) operational stage (7-11) formal operational (11+). These stages move us from learning about the environment by touching and moving objects through it, to the development of language where we begin to apply symbolism and acquiring the concept of an ideal world. From this stage we start making rational judgments about concrete or observable phenomena using language to manipulate symbols. At the last stage we develop hypothetical and deductive reasoning. Increasingly more complex processes are incrementally added to the previous stages established in earlier stages of our development.

The model that we build in our mind is similar to how scientists organize the world in terms of classes of objects or schemas.  Improving upon existing schemas through a process of logical assimilations or by changing the schema through accommodation this process aims for equilibrium--what Piaget terms “equilibration.”  The beauty of this type of thinking is that intelligence is a reflection of an active process. Our brain is forming a model of the outside world that helps us understand and predict the world. And there are specific developmental stages in how we do this.

But Piaget stopped at young adulthood and he stopped at the cognitive. In a world of “hypercognitive snobbery”—where cognition is prized above other equally valuable aspects of being identified in 2006 by Stephen Post p.223—we assume that thinking is the ultimate, but cognition is not comprehensive enough to explain our world. We also have an emotional component in living, perhaps more important, but surely as important.

As with the current thinking at the turn of the 20th century, “old age” was seen as a decline from a peak of early adulthood. Piaget, following this prejudice, did not think that much happens after attaining formal operational stage. But he was wrong.

There is, at least, another stage of reasoning that we can also identify.  The late Fredda Blanchard-Field with the Georgia Institute of technology promoted a stage of emotional development for older adults. What has developed into the socioemotional selectivity theory, this theory argues that we become more intelligent and mature about how we feel, where we select to remember positive experiences above negative ones. Pruning our social circles of friends or acquaintances and learning to let go of loss and disappointments are the external expression of this stage in thinking. But there is more. Our brain is wired so that the older we get the more that we focus and remember positive events while forgetting negative ones.

Psychologists Laura Carstensen—director of the Stanford Center on Longevity—and Charles Mather—with the University of California Santa Cruz—reported on neural mechanism that might be responsible for this selection of positive emotions. They identified cases where the amygdala—a small almond sized structure deep within the two sides of the brain—seems to be activated differently by younger versus older adults. Younger adults activate this structure more for negative images while older adults had higher activation for positive images.

But this did not explain why older adults remembered positive experiences better. It took a New Zealand psychologist Donna Addis and her colleagues to identify a possible mechanism. They asked young and older adults to view a series of photographs with positive and negative themes while recording their brain activity (fMRI). They found that in older adult brains, two regions that are linked to the processing of emotional content were strongly connected to regions that are linked to memory formation. Suggesting that older adults remember the good times well because the brain regions that process positive emotions also process memory.

Older adults experience an increase in positive thoughts and feelings, along with a decrease in negative emotions like anger and frustration. Living longer makes you remember positive emotions better because we are engineered that way—Genetic Epistemology. Like Piaget’s stages of cognitive development, this socioemotional stage involves a qualitative difference in how we process our environment.  Reclaiming older adulthood as a unique stage in our development—rather than seeing older age simply as a decline—dictates that we assign this socioemotional selectivity stage on equal basis with the other stages of development. We cannot learn a specific concept if our mind has not yet developed the capacity to understand it. We need to mature to learn how to interpret emotional reality.

References.

Isaacowitz, DM & Blanchard-Fields, F. (2012). Linking Process and Outcome in the Study of Emotion and Aging. Perspectives on Psychological Science, 7(1), 3-17

Piaget, J. (1970). Genetic Epistemology. New York: Norton.

Piaget, J. (1977). Gruber, H.E.; Voneche, J.J. eds. The essential Piaget. New York: Basic Books.

Piaget, J. (1983). Piaget's theory. In P. Mussen (ed). Handbook of Child Psychology. 4th edition. Vol. 1. New York: Wiley.

Post, SG. (2006). Respectare: Moral respect for the lives of the deeply forgetful. In J. C. Hughes, S. J. Louw, & S. R. Sabat (Eds.), Dementia: Mind, meaning, and the person (pp. 223–234). Oxford: Oxford University Press.

© USA Copyrighted 2016 Mario D. Garrett

The Fallacy of the Epidemiological Transition

​History dictates that with a changing population structure there is a parallel mirror process affecting health. The theory behind population change is called the demographic transition, while the historical change in mortality is called the epidemiological transition [1].   Epidemiological transition piggybacks on an established mathematical theory that argues that populations go through a cycle of high death and high birth rate, followed by declining death rate and declining birth rate.  Finally reaching a stage characterized by very low birth rate and low but fluctuating death rate.  The epidemiological transition posits that throughout this cycle mortality changes from infectious diseases to chronic disease. Finally reaching a stage of delayed chronic diseases. Unlike the distinct definitions of fertility and death rate that determine the demographic transition, the cut-off between an infectious disease and a chronic disease has become blurred.

In the United States, according to the Centers for Disease Control and Prevention (USA-CDC) more than seventy percent of all deaths are due to chronic diseases [2] .  Chronic diseases are characterized by Alzheimer’s disease, heart disease, diabetes and cancer. Since the causes of chronic disease was argued to be a combination of genetic, environmental, or lifestyle factors, public health was relegated as unimportant in dealing with chronic diseases. Public health is something that concerns only developing countries, until this year.

When an accountant managed water quality in Flint, Michigan, we very quickly saw a public health disaster enfold. Resulting in tainted water that marred the lives of a countless number of children for the rest of their lives. We created a chronic problem from a public health disaster.  So perhaps we need to revisit the epidemiological transition, since infectious diseases might also contribute to chronic diseases.  Especially since we are finding that chronic disease may apparently be infectious after all. If we can show that chronic diseases are infectious then the epidemiological transition becomes irrelevant.

An increasing number of chronic diseases are coming under scrutiny as possibly caused by infections. There are multiple examples to support the view that chronic diseases are in fact infectious diseases with a delayed expression. However, the search for bacterial, viruses, or environmental toxicity causes is difficult. Primary difficulty lies in detecting and replicating the causative agents in the laboratory. In most cases there are lags between the infection and the expression of the disease. Sometimes by the time the symptoms of the chronic disease appear, the causative agent is no longer present. But there are already strong signs that the three main chronic diseases have elements of infections: Alzheimer’s disease, cancer and heart disease.

Alzheimer’s disease

The initial infection that starts Alzheimer’s disease is unknown. As a chronic disease most of the research focuses on genetic mechanisms. But there is growing evidence that other, more relevant mechanisms exist, especially if we look at Alzheimer’s disease as a public health concern. These mechanism are: viral (HIV/AIDS, herpes simplex virus type I, Varicella zoster virus, cytomegalovirus, Epstein-Barr virus), bacteria (syphilis and Lyme-disease/borrelia), parasites (toxoplasmosis, cryptococcosis and neurocysticercosis), behavior (Alcohol, cigarette smoking, recreational drugs, concussion/mild/severe brain trauma) environmental elements (possibly aluminum), infections (possibly prions such as in Cretchfeldt-Jakobs disease), vascular causes (stroke, multiple-infarct dementia hydrocephalus, and injury or brain tumors, and emotional trauma. There are numerous studies that correlate all of these factors with Alzheimer’s disease, but surprisingly none of these factors appear in the federal “guidelines” for Alzheimer’s disease. [3]

As an example of the likely bacterium connection to Alzheimer’s is Lyme disease. Alois Alzheimer—who identified the disease in 1907—was primarily interested in syphilis. For centuries, other than just old age, syphilis was the main and only known cause of dementia. Although neurosyphilis is rare today, another bacterium gaining interest is Lyme disease. Lyme dementia has become a greater concern because it is the most common vector-borne disease in the northern hemisphere. Since there is no cure the expectation is that more patients will develop Lyme dementia in the near future [4].

Cancer

Other example where an infectious or an environmental substance contributes to chronic diseases is cancer. Viral causes of cancer are common enough that we call viruses that can cause cancer an oncovirus. These include human papillomavirus (cervical carcinoma), Epstein-Barr virus (B-cell lymphoproliferative disease and nasopharyngeal carcinoma), Kaposi's sarcoma herpesvirus (Kaposi's Sarcoma and primary effusion lymphomas), hepatitis B and hepatitis C viruses (hepatocellular carcinoma), and Human T-cell leukemia virus-1 (T-cell leukemias).

Bacterial infection may also increase the risk of cancer, as seen in Helicobacter pylori-induced gastric carcinoma. Parasitic infections strongly associated with cancer include Schistosoma haematobium (squamous cell carcinoma of the bladder) and the liver flukes, Opisthorchis viverrini and Clonorchis sinensis (cholangiocarcinoma.)

The human papillomavirus, for instance, causes more than 90 percent of cervical cancer cases and is one of the most common cancers in the world especially in Asia. With childhood immunization programs, including the hepatitis B vaccine, this cancer will become less prevalent. Hepatitis C virus causes cirrhosis, end-stage liver disease, and liver cancer. Human herpesvirus 8 causes Kaposi’s sarcoma, a malignant complication of AIDS. Helicobacter pylori, a spiral-shaped bacterium, is the agent of peptic ulcers and gastric cancer and has an important  story of resistance, although not biologically but politically.

In 2005, two Australians, Barry Marshall and Robin Warren were awarded the Nobel Prize in Physiology for their pioneering work identifying the bacterium Helicobacter pylori as the cause of peptic ulcer disease. Overnight peptic ulcer disease was no longer a chronic disease but an infectious disease that can be cured by a short regimen of a pair of antibiotics. But despite evidence, it took more than ten years to persuade the scientific community. At the end, it took the primary author, Barry Marshall to infect himself with the bacteria to prove his point to a disbelieving scientific community. The long held view that peptic ulcer disease was a chronic disease wrestled against any competing views that it might be infectious.

Heart Disease

The relationship between heart disease and bacteria/virus is still sparse and interpretation of results is limited by potential biases. A large number of studies have reported on associations of human coronary heart disease and certain persistent bacterial and viral infections. One concluded that the relationship of heart disease with H pylori is weak, while for C pneumoniae, the evidence of association is stronger but still uncertain  [5].  Endocarditis is a disease characterized by inflammation or infection of the inner surface of the heart usually caused by a bacterial infection from the mouth that enters the heart.

And there are already evidence for the efficacy of an approach that looks at chronic disease as caused by infections. At the 2016 annual meeting of the American Association for the Advancement of Science, Stanley Riddell with Seattle's Fred Hutchinson Cancer Research Center, announced how T-cell therapy can help the human immune system fight off cancer cells the way it would attack foreign bacteria or a virus. This finding joins the arsenal of some vaccines to prevent cancer.

Such associations have been difficult to expose because the path from exposure of an infection to the expression of the chronic disease is usually not linear. There are other mediating or/and moderating factors. For example, the role of infection mediated through chronic inflammation is then associated with a variety of chronic diseases such as multiple sclerosis, rheumatoid arthritis, lupus, and other autoimmune diseases. But the pharmaceutical industry, despite their advantage at being able to “cure” chronic disease has been reticent in accepting the full force of this implication. It is not a clever economic strategy to cure diseases, only to manage them.

What we need is a broader approach to look at cancer, heart disease and Alzheimer’s disease more as a public health concern. Looking at chronic disease as a long-term assault from an external agent, whether this agent is a bacterium, virus or some toxic element. By re-addressing our priorities in research, perhaps this is the way out of this research cul-de-sac we find ourselves in. It is such radical thinking that is needed to hopefully start finding cures that have evaded us so far.

References

[1]   Omran, A.R (2005. First published 1971), "The epidemiological transition: A theory of the epidemiology of population change" The Milbank Quarterly 83 (4): 731–57, doi:10.1111/j.1468-0009.2005.00398.x

[2]  Centers for Disease Control and Prevention. Death and Mortality. NCHS FastStats Web site. http://www.cdc.gov/nchs/fastats/deaths.htm. Accessed December 20, 2013.

[3] Garrett MD, Valle R (2015) A New Public Health Paradigm for Alzheimer’s Disease Research. SOJ Neurol 2(1), 1-9.

[4] Blanc F,Philippi N,Cretin B,Kleitz C,Berly L,Jung B,de Seze J. Lyme Neuroborreliosis and Dementia. Journal of Alzheimer’s Disease 2014; 41(4):1087-1093.

[5] Danesh, J., Collins, R., & Peto, R. (1997). Chronic infections and coronary heart disease: is there a link?. The lancet, 350(9075), 430-436.

© USA Copyrighted 2016 Mario D. Garrett

A New Paradigm for Alzheimer's Disease Research

From lost hope emerges a new perspective. After more than a century of research into Alzheimer’s disease we have reached a research cul-de-sac. By eradicating the plaques and tangles from the brain, a series of studies reported that the disease worsened ^1,2. What this tells us is that the disease is more complex then just a build up of mis-folded proteins.

In panic, the National Institute on Aging, coopting the Alzheimer’s Association, published new guidelines for Alzheimer’s disease in 2011.³  These guidelines effectively transformed a clinical disease--a disease defined by its behavioral manifestations—into a pre-clinical disease. What this means is that now Alzheimer’s disease exists before there are any clinical manifestations. This seems counterintuitive given the studies showing that drugs that cleared the plaques and tangles—the only pre-clinical indicators--did not cure Alzheimer’s disease and in fact made it worse. But the increasing power of the pharmacological industry in establishing the research agenda seems limitless. Now pharmaceutical companies can experiment with patients before they even start showing symptoms of the disease. In effect, curing a disease before the clinical disease emerges. But so far, they have had little success. 

Since the early 1990 pharmaceutical companies have been attempting to halt early onset dementia among an unfortunate community in Medellin, Colombia. Discovered by Francisco Lopera in 1984, this heritable variant of Alzheimer's disease share a common ancestor—a 16th-century Spanish colonist who to this day has infected 5,000 patients in 25 families. ⁴  The reason why this approach—trying to find a biological cause of the disease--has been so resilient despite mounting evidence contradicting this approach, is that there has not been a competing theory to challenge it. Until now.

A crescendo of mounting criticism has established that Alzheimer’s disease is more complex than a cascade of misfolded proteins. That even though people might have the plaques and tangles, some do not express the disease, while some who express Alzheimer’s disease have been shown to have no significant plaques and tangles. In addition, with older adults, multiple studies have shown that the correlation between plaques and tangles and Alzheimer’s disease declines with age. One way to explain these anomalies is to broaden the study of Alzheimer’s disease. One such approach is to see it as a public health disease. ⁵

A public health perspective argues that there are multiple traumas to the brain. Some of these can be a virus or bacteria, while some are physical (like a concussion). We are seeing more and more how physical trauma causes dementia among NFL football players. But sometimes this trauma is managed and contained. A good example of this process is looking at stroke victims where we see more than 30 percent improving. In such cases, the penumbra—the protective cells that surround the initial trauma—is contained and the death of cells remains localized. Two factors promote this healthy brain. One is blood supply—Perfusion, while the other is growing your brain--Plasticity.

Perfusion allows for the brain to receive adequate nutrients and energy to heal itself. Having a healthy brain improves the chances that a trauma is contained. Plasticity on the other hand ensures that there is enough flexibility in the brain that if the brain needs to contain an area that other parts can take over that lost function. Without these two factors the penumbra will continue to grow and affect larger areas of the brain—and such damage will go beyond plaques and tangles. This broader public health interpretation of Alzheimer’s disease assimilates both the traditional Amyloid Cascade hypothesis and explains the increasing number of studies showing how external factor influence the incidence of Alzheimer’s disease.

The beauty of this public health approach is that we do not have to wait another hundred years before we realize that we are in a research cul-de-sac. We can start implementing programs that reduce and lower the exposure to traumas. Reduction of concussions (in sport, military, recreational activities) should be made a priority. Programs that educate on the effects of smoking and heavy drinking on the brain need to be promoted, as well as programs that address environmental toxicity both in the air and in our water. For perfusion, city walkability programs, and social engagement programs all promote walking, swimming, light exercise, gardening among other activities. While improving plasticity involves social activities, dancing, music and other cognitive exercises.

Pharmaceutical influence can determine federal research policy, but with knowledge, individuals can protect themselves and their family from exposure to this deadly disease that we still do not fully understand.

A version of this article can be found in:

Garrett MD & Valle R (2015) A New Public Health Paradigm for Alzheimer’s Disease Research. SOJ Neurol 2(1), 1-9. Page 2 of 9.

A complete story of this blog can be found in my recently published book: 

Garrett MD (2015).The Politics of Anguish: How Alzheimer’s disease became the malady of the 21st century.

References.

1. Gilman S., Koller M., Black R.S., Jenkins L., Griffith S.G., Fox N.C, et al. (2005). Clinical effects of Abeta immunization (AN1792) in patients with AD in an interrupted trial. Neurology, 64:1553–62.

2. Boche D., Donald J., Love S., Harris S., Neal J.W., Holmes C., et al. (2010). Reduction of aggregated tau in neuronal processes but not in the cell bodies after Abeta42 immunisation in Alzheimer’s disease. Acta Neuropathol, 120: 13–20.

3. Jack  C.R., Albert M.S., Knopman D.S., McKhann G.M. Sperling R.A., Carrillo M.C., ... & Phelps C. H. (2011). Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's & Dementia, 7(3):257-262.

4. Lopera F., Ardilla A., Martínez A., Madrigal L., Arango-Viana J.C., Lemere C.A., ... & Kosik K.S. (1997). Clinical features of early-onset Alzheimer disease in a large kindred with an E280A presenilin-1 mutation. Jama, 277(10): 793-799.

5. Garrett MD & Valle R (2015) A New Public Health Paradigm for Alzheimer’s Disease Research. SOJ Neurol 2(1), 1-9. Page 2 of 9

© USA Copyrighted 2016 Mario D. Garrett

Bad Drugs and Older Adults

Bad Drugs

Drugs work in mysterious ways. Sometimes it benefits us, other times there are negative side effects. Half of all adverse drug occurs when five or more drugs are taken and it is nearly certain that there will be a reaction when eight or more drugs are taken. How dangerous can this be?

Sometimes prescribed medications cause death. The Danish physician and researcher Peter C. Gøtzsche from the Nordic Cochrane Centre, estimates there are 15 times more suicides among people taking antidepressants than are reported by the US Food and Drug Administration. By looking at Danish prescription statistics for antipsychotics, benzodiazepines, and antidepressants he estimated that the death rate for older adults was between 1 and 2 percent.  Based on these Danish death rates he estimates that for the U.S. and European Union combined an estimated 539,000 older adults die from these drugs every year. But it is not just antidepressants that can cause adverse reaction. Especially with older adults because our metabolism changes with age, the filtering of the drug in our bodies is compromised and becomes less efficient. Drugs remain in our blood longer. As a result, the effect of drugs changes as we age.

Every few years the American Geriatrics Society (AGS) releases an updated and expanded Beers Criteria (after the originator of the first list, Mark Beers)--a list of potentially inappropriate medications for older adults that is developed from reviewing over 6,700 clinical studies. The report is complex, technical and detailed and needs to be reviewed with your physician. However, as a summary, it is important to realize how common bad side effects are for most of the medications that we take.

For example, among patients aged 65 years and older, insulin or warfarin (Coumadin®) was the cause of one in every three drug reactions that resulted in an emergency hospital visit and was responsible for nearly half of all drug reaction hospitalizations. Analgesics for chronic pain cause slowed breathing and caused constipation. NSAIDs, such as ibuprofen (Advil®) and naproxen (Aleve®), are generally not recommended for the older adults because of stomach and intestine irritation and possibly raising blood pressure. While acetaminophen (Tylenol®) increased the risk of hypertension by a third. Some medication prescribed for schizophrenia and bipolar disorder Aripiprazole (Abilify®), clozapine (Clozaril®), and risperidone (Risperdal®) may increase blood sugar indirectly due to weight gain. Decongestants and other anticholinergics that we can get at the pharmacy without a prescription can cause confusion, urinary retention and other problems. For example Pseudoephedrine (Sudafed®) can raise blood pressure. Researchers found that half of all older adults taking anticholinergics showed mental decline.  Beta-blockers like Atenolol (Tenormin®), sotalol (Betapace®) prescribed for hypertension, arrhythmias, and thiazide diuretics, such as chlorothiazide (Diuril®) and indapamide (Lozol®) prescribed for hypertension and congestive heart failure can increase the risk of diabetes. Corticosteroids such as prednisone and methylprednisone (Medrol®) prescribed for arthritis or asthma increase blood sugar and can lead to type 2 diabetes. Erectile dysfunction medications like sildenafil (Viagra®), tadalafil (Cialis®) and other medications may cause visual and hearing disturbances. The biggest category of drugs taken by older adult  is statins for cholesterol, where atorvastatin (Lipitor®), simvastatin (Zocor®) and other statins may create very low levels of cholesterol that may lead to depression, memory loss and confusion. Some statins may cause liver damage. Congestive heart failure medications such as digoxin (Lanoxin®) and diuretics are at risk for electrolyte imbalances and therefore risk poisoning the body through increased toxicity. Hip fracture is increased among elderly patients who take proton pump inhibitors such as lansoprazole (Prevacid®), esomeprazole (Nexium®) and omeprazole (Prilosec®) and to a lesser extent by H2-blockers such as cimetidine (Tagamet®) and famotidine (Pepcid®).

Because so many medications are excreted via the kidney, it is important for elderly patients to have kidney function assessed regularly. Impaired kidney function may require adjustment of medication dosages. What we eat can also influence how these drugs react in our body. Certain drugs have dietary implications, including foods to avoid and nutrients that are essential. Some medications should be taken on an empty stomach, some with food.

Older adults also use drugs that they buy from the dispensary without getting a doctor’s prescription. These “over-the-counter” drugs are readily available, and people again feel that they are safe. Nearly half of prescription users also take at least one over-the-counter medication. In addition, there is an increased use of herbal or dietary supplements (eg, ginseng, ginkgo biloba extract, and glucosamine) by older adults. Almost three-quarters of older adults use at least one prescription drug and one dietary supplement. Sometimes we do not tell our doctor that we are taking these supplements because we think they are not important. But herbal medicines may interact with prescription drugs and lead to adverse events. Such adverse events as when ginkgo biloba extract is taken with warfarin, causing an increased risk of bleeding, or when St. John's wort is taken with serotonin-reuptake inhibitors, increasing the risk of too much serotonin causing symptoms ranging from mild (shivering and diarrhea) to severe (muscle rigidity, fever and seizures). Severe serotonin syndrome can be fatal if not treated. A study of the use of 22 supplements found potential interactions between supplements and medications in half of these supplements.

We do not know all of the ill effects of medications on older adults, especially among older women, because these drugs are rarely, if ever, tested among older adults. The drug-drug interactions, side-effects, cost of medications, medications that should have been stopped ages ago, and medications that are inappropriate for older adults suggest that the fewer drugs you take the safer you are. Some people cannot reduce their medications, but by discussing your medications with your physician, you can start the discussion to try and reduce and possibly eliminate some of your drugs. In some cases replacing medication with other treatments, such as psychotherapy, exercise, social activities or some behavior modification training might be worth exploring especially for behavioral concerns. For some who have found a balance, their medication regime is sustaining life. But it seems that there are many others who are struggling to find this balance.

© USA Copyrighted 2016 Mario D. Garrett

Death of Happiness Greatly Exaggerated

We are a “clicking” nation. We measure how important ideas are by the veracity of readers’ “like” “share” or comments. In response to this reality, newspapers’ headlines are dramatic and “clicking good”. Becoming increasingly common however, is that such click-baiting headlines rarely reflect the content of the news items. Human foibles promote the constant search for dramatic new insight, in contrast to the slow dribble from the fountain of knowledge.

A case in point is a paper published in the esteemed medical journal Lancet this year. The news reports went ecstatic with this news, within a few days reports spread across the globe with 402 newspaper and magazine headlines reporting: “Million Women Study: Happiness does not guarantee a long life” (Times UK-Dec 10, 2015); “Happiness is not the key to a long life” (Independent Online-Dec 10, 2015); “Happiness Doesn't Bring Good Health, Study Finds”(New York Times-Dec 9, 2015); “Happiness Doesn't Help You Live Longer” (The Atlantic-Dec 9, 2015); “Being happy doesn't make you live longer, research says” (The Independent-Dec 9, 2015); “Is Happiness Really Linked To Longevity? Maybe Not, Study Finds” (Forbes-Dec 10, 2015). In one short article, and a contagion of newspaper headlines, a century of work that has consistently shown the importance of happiness for longevity have been ignored or discarded. We “clicked” happiness to death. But this might have been exaggerated.

The original paper [1], conducted by Bette Liu with the Faculty of Medicine, University of New South Wales, Australia and her colleagues, had an interesting methodology. The short abstract—on which most newspapers must have based their compelling news reports—concluded: “In middle-aged women, poor health can cause unhappiness. After allowing for this association and adjusting for potential confounders, happiness and related measures of wellbeing do not appear to have any direct effect on mortality.” Being miserable is cool and it does not hurt you. But before you throw away your Prozac, lets examine what these researchers did and see if we can come up with different and more articulate interpretation of the data.

This study was based on the Million Women Study, a study of 1.3 million UK women in their 50s who went for a mammogram—recruited between 1996 and 2001—looking at future cancer incidence after taking Hormone Replacement Therapy. In the past, the results based on this database have been controversial. The overall findings have found lifestyles, habits or behaviors as remembered and recalled by participants in their youth have less an affect on cancers, heart disease or other illnesses than present lifestyle choices.  Basically arguing that—other than radiation—the present is more important than the past. This goes against the whole field of epigenetic studies and how lifestyle and diet choices have long lasting effect, sometimes across multiple generations.  But one of the problems with this database is that they are dealing with recall and self-perception. How we recall events tend to come in-line with our present reality. 

Returning to this specific article on happiness, heralding the importance of happiness, surprisingly the authors found that in all the results, being happy most of the time faired better on ALL variables. No exceptions. While being unhappy was associated with higher mortality—even after adjusting for age, which influences probability of death—by 30 to 40%. Despite these dramatic correlations, the authors still conclude that: “After allowing for this association and adjusting for potential confounders, happiness and related measures of wellbeing do not appear to have any direct effect on mortality”. The fact that the authors were able to whittle away all of the very positive correlates of happiness to leave a shriveled edifice of happiness, holding no predictive power, attest to how skilled the authors are at playing with statistics. Within a clinical database, the authors undress happiness until its emptiness is exposed. But what is happiness without its expression?

It is not the statistics that is questionable but the authors’ methodology. This type of analysis is referred to as “kitchen sink” analyses. Chuck everything in and see what comes out. Results are not theory driven but motivated by spurious and random associations. Eliminating correlates of happiness away—within a very limited, clinical database—happiness becomes irrelevant. But happiness is an collection of evaluations of how content we are in life. It is made up of individual components, with our evaluation of our health forming a main aspect of our happiness.

Because the authors found that happiness was related to all positive variables, they did something very strange. They adjusted happiness. Within logistic regression—which tests the effect of a condition/s (or independent variable) on a yes or no outcome (dependent variable, which in this case was dead or alive) you adjust variables by modifying the outcome to match the condition and thereby eliminating the effect of one independent variable on the dependent variable. This is important because you can isolate an individual variable and see how it behaves regardless of all other variables. Which is what the authors did for happiness.  First they broke up the groups into three main groups and then they started eliminating variables sequentially to see which one will mute the effect of happiness. They did this by diluting their construct validity, and then by reverse engineering happiness. Let me explain.

The first methodological fault is massaging their definition of “unhappy”. Out of 719,671 women with a median age 59 year, 39% reported being happy most of the time while the majority (44%) reported being happy usually, while the final group was defined as rarely reporting happiness. But this is not accurate. This final group was composed of three very distinct categories of people who reported being either happy sometimes, rarely or never. Far from being a homogenous group this category is a subjective potpourri of a group of sensible people who report that they do sometimes feel happy, combined with—according to the DSM-V—a clinically diagnosable group who are likely depressed and report never to be happy. So this is a strange mixture of people grouped together and called “unhappy.”  Methodologically, the authors should have selected only the never feel happy group. They are a distinct group. But by lumping all three categories together they lost construct validity. We do not know what they are comparing the happy group against.  When they refer to the “unhappy” group a proportion of these are happy sometimes.

They continued to dilute the construct validity by excluded the first five years of follow-up and women who had already had heart disease, stroke, lung disease, or cancer. We do not know why these people were excluded but it is likely that these very ill women were likely to be the least happy and the most clinically depressed (based on their own data of who these women are because the strongest associations with reported unhappiness were treatment for depression or anxiety and reporting only fair or poor general health). By eliminating them the authors got rid of the negative outliers, further diluting the construct to include people closer to the average. By including “sometimes happy” people in the group of “unhappy” people, and then eliminating the extremely unhappy people, what the authors did is to dilute the construct of “unhappy” to produce a group that is closer to the average.  

The second methodological fault is the reverse engineering of happiness. After finding that happiness is positively correlated with all healthy indicators, the authors proceeded to strip away these variables. This is known as adjusting the data. The authors adjusted the data for a number of factors. In regression analyses such adjustments create ceteris paribus, a Latin term meaning “all else being equal.” So when you adjust for variables you even out—eliminate the affect of—that variable. Practically you are throwing these variables out of the effect. Such statistical techniques are important when you want to see if one variable is important by itself accounting for the effect of all the other variables separately. But in this case we have to question the number of variables that were adjusted to minimize happiness. Theoretically in psychology, happiness is not a stand-alone construct but an omnibus construct reflecting a number of individual components. If you eliminating these recorded expressions—and the Million Women Study database is limited in how happiness is recorded—then there are few variables that are correlated. Being happy was correlated with increasing age, having fewer educational qualifications, doing strenuous exercise, not smoking, living with a partner, and participating in religious and other group activities. 

Only when the authors eliminated ALL the correlated of happiness that exist in their database did happiness become an emaciated variable with no meaning. The authors first adjusted only for age. Then they continued to adjust for region of residence at recruitment including employment, car ownership, home ownership, and household overcrowding, college and pre-college education, living with a partner, whether they are obese, perform strenuous exercise, smoke, drink alcohol of one drink a day, participation in religious or other group activity. None of these activities diminished the effect of happiness, which tells us that happiness is expressed in people who are not defined by any of these categories. The only variable that seems to mimic or act as a proxy for happiness is self-rated health (in their Table 2).

In summary the three adjustments that got rid of the happiness factor:

Eliminate all the really depressed and sick people. Eliminating over 125 769 women who at baseline already had heart disease, stroke, cancer, or chronic obstructive airways disease. These excluded women who had three times the death rate. Again, it is very likely that this group of women were the most depressed and unhappy.
Diminish the effect of older adults who are normally happy. By adjusting for age we are reducing the effect of happiness. We know that the older we become the happier we are. Such consistency data that has economists interested in psychology because it determines economic behavior. Despite this adjusting for age, happiness still emerged as a resilient factor in reducing mortality. Adjusting only for age, unhappiness remained associated with 25-33% increase in death.
Only by getting rid of self-rated health did the effect of happiness completely vanished. Translated this means if we eliminate the importance of how healthy or unhealthy participants felt, then it does not matter how miserable you are in determining your mortality.

But after adjustment for self-rated health, treatment for hypertension, diabetes, asthma, arthritis, depression, or anxiety, lifestyle factors—including smoking, deprivation, and body-mass index— unhappiness was not associated with mortality from all stress or lack of control.

In psychology, happiness is relatively stable, while unhappiness is more variable [2]. Similarly the authors of this study reported that there was some instability in happiness figures, especially from being unhappy to becoming happy a year later.  While only 2% who reported being happy most of the time at baseline changed to being unhappy at follow-up, 5% of women who reported being unhappy at baseline reported being happy most of the time a year later. This is a gain of 3 % per year (difference between becoming happier to becoming sad). From their own study the results show that very year, there is an improvement on happiness of 3%.

Dariusz Leszczynski, a Polish cell biologist wrote in the Washington Times Communities, Oct 3, 2013 that “The Million Women Study has shoddy exposure design leading to shoddy results and ending with shoddy conclusions.”  Applying a database to study relationships other than what the database was original developed for is not inherently bad science. But when there are complex constructs such as happiness, that are not fully understood, having a million or more women who went in for a mammogram might not be a representative group to generalize from. The limitation in external validity is significant.

Happiness is a central emotional indicator that brings our body and mind in balance. It is one of the main predictors of mortality that even economists and actuaries apply to adjust their mortality forecasts based on the present level of happiness and self-rated health. If there is one objective in life it is to be happy, everything else is peripheral. Attempting to summarily dismiss a century of research [3]—that has been trying to understand the meaning of happiness and longevity—needs to be questioned.

Citations

[1] Liu, B., Floud, S., Pirie, K., Green, J., Peto, R., Beral, V., & Million Women Study Collaborators. (2015). Does happiness itself directly affect mortality? The prospective UK Million Women Study. The Lancet.

[2] Veenhoven, R. (1994). Is happiness a trait?. Social indicators research,32(2), 101-160.

[3] Lucas, R. E. (2007). Personality and the pursuit of happiness. Social and Personality Psychology Compass, 1(1), 168-182.

© USA Copyrighted 2015 Mario D. Garrett