Understanding population-level genetic interactions for neurodegeneration in the Indian Population

People worldwide suffer from a plethora of neurodegenerative diseases, yet the pathogenesis of most of these diseases is not fully known. Neurodegeneration is the result of the loss of function of neurons and their progressive atrophy. Many of the body’s activities, such as movement, balance, memory, and cognition, can get impaired due to neurodegeneration, because of which patients can become entirely dependent on caregivers. There is the Global Burden of Disease Study (GBD), where over 6500 researchers from more than 155 countries conduct a collaborative effort to quantify the burden of various diseases. As per a GBD study, as of 2016, Alzheimer’s disease and Dementia contribute 10.4% to disability-adjusted life years (DALYs). This metric refers to the sum of years lived with disability and years lost due to premature death. Neurodegeneration is primarily heritable and is a multigenic, multifactorial, and complex trait. One of the most significant risk factors is increasing age. Because neurodegenerative diseases manifest in mid to late life, as the population ages, the number of cases is expected to rise unless prophylactic and therapeutic interventions are discovered. While past studies have indicated that maintaining a healthy lifestyle impedes disease progression, individuals already carry a certain risk of predisposition to neurodegeneration depending on their genetic makeup. It is known that the human apolipoproteinE (APOE) gene, along with other genetic risk loci, confer high risk for neurodegeneration. But they account for only a certain percentage of heritability (for instance, 0.24-0.53% in case of Alzheimer’s disease). Thus, it is essential to identify additional genetic risk factors, their interactions among themselves as well as the environment, and the pathways involved to explain more of this heritable condition. While evidence suggests APOE gene to be the major predisposing factor for neurodegeneration, the mechanism by which it contributes to onset and progression is unknown, and that is why no medication has been discovered that can prevent inception or stop disease advancement. Thus, an important research question is to identify the genetic loci working in conjunction with APOE in humans via their functions in putative pathways which have been hypothesized, on the basis of mouse-model as well as functional studies, to play a role in manifesting cognitive impairment in neurodegeneration. Large-scale human population-based association studies with samples that are indeed representative of the population can provide more reliable evidence of disease pathogenesis in a cost-effective manner. My work focusses on the Indian and European population with the critical objectives of implicating genetic variants associated with APOE in symptoms of neurodegeneration and determining their downstream causal pathways considering underlying interactions comparing results across global cohorts to identify population-specific differences in genome architecture accounting for differences in disease manifestation. 

Most population-based association studies have focussed on cohorts with western ancestry, but no human population-based study has been focussed on the Indian population. Due to evolutionary and environmental factors, the genetic makeup of the Indian population is expected to be different. So far, no such large-scale studies based entirely on the Indian population have been conducted. This study can set an example and identify novel gene locations and susceptibility loci for neurodegeneration specific to the Indian population compared to European population. Uncovering such novel locations can unleash preventive and therapeutic strategies that could be better suited in terms of efficacy for the Indian population and pave the way to precision medicine. Interactions at the population scale to understand the disease etiology beyond the contribution from single genetic-variant effects are rarely studied. While elucidating the disease mechanism, this interaction network knowledge at the genetic level will also help to uncover additional genetic risks that can explain the heritability of neurodegeneration better and the reasons for differential results (if any) among populations. 

We identify genetic variants acting in conjunction with APOE  to influence cognition while teasing out effects of other age-associated metabolic risk factors like dyslipidemia and glycemic imbalance co-occuring with age based on a whole exome-wide study on 157,160 individuals. We detect 18 previously unknown genetic variants in this context, that could influence five cognition domains. We also identify overlapping association hits when we restrict our study to coding regions only. We further identify two lipid-transport genes - APOC1 and LRP1 associated with two domains of cognition, namely complex processing speed and visual attention. We also find hitherto unknown interactions between APOE and other variants in AMIGO1 and other loci, which could affect episodic memory, simple processing speed, and visual attention, even while controlling for metabolic risks. Besides these independent effects, we uncover mediating and pleiotropic effects of these variants on cognition and metabolic risks. All the significant variants and genes we uncover show high expression in the brain and are essential for functions that correlate with neuronal mechanisms underpinning cognition. From the distinct association results for each of the cognitive domains, our results emphasize the need to study the genetic architecture of cognitive functioning at a more granular domain-specific level.

Our preliminary work on epistasis analysis was carried out for genome-wide body mass index (BMI) associated SNPs in Alzheimer’s Disease Neuroimaging Initiative (ADNI), with top significant interacting SNPs followed up in the UK Biobank imputed genotype dataset with more than 188,000 samples. We tested a consensus of nine different epistatic tools which implemented exhaustive, heuristics, stochastic  and machine-learning approaches, and discovered two pairwise epistatic interactions, one between rs2177596 (RHBDD1) and rs17759796 (MAPK1), and the other between rs1121980 (FTO) and rs6567160 (MC4R). These two pairwise epistatic interactions signify neuronal influence in obesity. This study suggested concerted expression of associated genes in metabolic abnormalities characterized by obesity, and highlighted the importance of understanding the effect of concurrently interacting genetic loci in disease aetiology, beyond single locus effects.