Genetics of Type 2 Diabetes: the Power of Isolated Populations

Birthweight and gestational age in the Faroe Islands: A comparison between birthweight and gestational age in the Faroe Islands and other Nordic countries

INTRODUCTION

This study aimed to examine Faroese infants' birthweight and gestational age in 2010-2019 and compare these findings with other Nordic countries. Risk factors for high birthweight among Faroese infants were also investigated in this study.

MATERIAL AND METHODS

All singleton liveborn infants registered in the Faroese Birth Registry in 2010-2019 were included in the study (n = 6121). A comparison was made with data on birthweight and gestational age from Denmark, Iceland, Norway, and Sweden.

RESULTS

The mean birthweight increased significantly from 3652 g (95% confidence interval [CI]: 3505-3699 g) in 2010 to 3745 g (95% CI: 3700-3790 g) in 2019, a mean increase in birthweight of 93 g (95% CI: 28-158 g) (p < 0.05). The birthweight increased 186 g (95% CI: 179-193 g) for each gestational week and 11 g (95% CI: 7-15 g) for each year. Changes in gestational age explained 31% of the change in birthweight. The proportion of infants weighing 4500 g or more increased significantly from 6.1% in 2010 to 9.6% in 2019 (p < 0.05). The risk of giving birth to an infant weighing 4000 g or more was consistently associated with previously giving birth (OR 1.98 (95% CI: 1.71-2.30)) and gestational age (OR 1.28 (95% CI: 1.23-1.33) per week increase in gestational age). Infants born in gestational weeks 40 and 42 in 2019 had a higher birthweight z-score than infants born in gestational weeks 40 and 42 in 2010. Compared to other Nordic countries, Faroese infants' mean birthweight was high, the Faroe Islands had a higher number of infants born with a weight of 4000 g or more and a higher proportion of infants born in gestational week 41 or later (31.5%).

CONCLUSIONS

Our results showed that the mean birthweight and the proportion of infants with high birthweight significantly increased during 2010-2019 in the Faroe Islands. The mean birthweight, the proportion of infants with high birthweight and the gestational age at birth for Faroese infants was higher than all other Nordic countries. The reasons for this require further investigation.

Identification of Type 2 Diabetes Biomarkers From Mixed Single-Cell Sequencing Data With Feature Selection Methods

Diabetes is the most common disease and a major threat to human health. Type 2 diabetes (T2D) makes up about 90% of all cases. With the development of high-throughput sequencing technologies, more and more fundamental pathogenesis of T2D at genetic and transcriptomic levels has been revealed. The recent single-cell sequencing can further reveal the cellular heterogenicity of complex diseases in an unprecedented way. With the expectation on the molecular essence of T2D across multiple cell types, we investigated the expression profiling of more than 1,600 single cells (949 cells from T2D patients and 651 cells from normal controls) and identified the differential expression profiling and characteristics at the transcriptomics level that can distinguish such two groups of cells at the single-cell level. The expression profile was analyzed by several machine learning algorithms, including Monte Carlo feature selection, support vector machine, and repeated incremental pruning to produce error reduction (RIPPER). On one hand, some T2D-associated genes (MTND4P24, MTND2P28, and LOC100128906) were discovered. On the other hand, we revealed novel potential pathogenic mechanisms in a rule manner. They are induced by newly recognized genes and neglected by traditional bulk sequencing techniques. Particularly, the newly identified T2D genes were shown to follow specific quantitative rules with diabetes prediction potentials, and such rules further indicated several potential functional crosstalks involved in T2D.

An LDLR missense variant poses high risk of familial hypercholesterolemia in 30% of Greenlanders and offers potential of early cardiovascular disease intervention

The common Arctic-specific LDLR p.G137S variant was recently shown to be associated with elevated lipid levels. Motivated by this, we aimed to investigate the effect of p.G137S on metabolic health and cardiovascular disease risk among Greenlanders to quantify its impact on the population. In a population-based Greenlandic cohort (n = 5,063), we tested for associations between the p.G137S variant and metabolic health traits as well as cardiovascular disease risk based on registry data. In addition, we explored the variant’s impact on plasma NMR measured lipoprotein concentration and composition in another Greenlandic cohort (n = 1,629); 29.5% of the individuals in the cohort carried at least one copy of the p.G137S risk allele. Furthermore, 25.4% of the heterozygous and 54.7% of the homozygous carriers had high levels (>4.9 mmol/L) of serum LDL cholesterol, which is above the diagnostic level for familial hypercholesterolemia (FH). Moreover, p.G137S was associated with an overall atherosclerotic lipid profile, and increased risk of ischemic heart disease (HR [95% CI], 1.51 [1.18–1.92], p = 0.00096), peripheral artery disease (1.69 [1.01–2.82], p = 0.046), and coronary operations (1.78 [1.21–2.62], p = 0.0035). Due to its high frequency and large effect sizes, p.G137S has a marked population-level impact, increasing the risk of FH and cardiovascular disease for up to 30% of the Greenlandic population. Thus, p.G137S is a potential marker for early intervention in Arctic populations.

A global genetic epidemiological review of pseudoexfoliation syndrome

Pseudoexfoliation (PXF) syndrome is an important public health concern requiring individual population level analysis. Disease prevalence differs by geographic location and ethnicity, and has environmental, demographic, genetic, and molecular risk factors have been demonstrated. Epidemiological factors that have been associated with PXF include age, sex, environmental factors, and diet. Genetic and molecular components have also been identified that are associated with PXF. Underserved populations are often understudied within scientific research, including research about eye disease such as PXF, contributing to the persistence of health disparities within these populations. In each population, PXF needs may be different, and by having research that identifies individual population needs about PXF, the resources in that population can be more efficiently utilized. Otherwise, PXF intervention and care management based only on the broadest level of understanding may continue to exacerbate health disparities in populations disproportionally burdened by PXF.

DNA Methylation and Type 2 Diabetes: Novel Biomarkers for Risk Assessment?

Diabetes is a severe threat to global health. Almost 500 million people live with diabetes worldwide. Most of them have type 2 diabetes (T2D). T2D patients are at risk of developing severe and life-threatening complications, leading to an increased need for medical care and reduced quality of life. Improved care for people with T2D is essential. Actions aiming at identifying undiagnosed diabetes and at preventing diabetes in those at high risk are needed as well. To this end, biomarker discovery and validation of risk assessment for T2D are critical. Alterations of DNA methylation have recently helped to better understand T2D pathophysiology by explaining differences among endophenotypes of diabetic patients in tissues. Recent evidence further suggests that variations of DNA methylation might contribute to the risk of T2D even more significantly than genetic variability and might represent a valuable tool to predict T2D risk. In this review, we focus on recent information on the contribution of DNA methylation to the risk and the pathogenesis of T2D. We discuss the limitations of these studies and provide evidence supporting the potential for clinical application of DNA methylation marks to predict the risk and progression of T2D.

Pseudoexfoliation and Cataract Syndrome Associated with Genetic and Epidemiological Factors in a Mayan Cohort of Guatemala

The Mayan population of Guatemala is understudied within eye and vision research. Studying an observational homogenous, geographically isolated population of individuals seeking eye care may identify unique clinical, demographic, environmental and genetic risk factors for blinding eye disease that can inform targeted and effective screening strategies to achieve better and improved health care distribution. This study served to: (a) identify the ocular health needs within this population; and (b) identify any possible modifiable risk factors contributing to disease pathophysiology within this population. We conducted a cross-sectional study with 126 participants. Each participant completed a comprehensive eye examination, provided a blood sample for genetic analysis, and received a structured core baseline interview for a standardized epidemiological questionnaire at the Salama Lions Club Eye Hospital in Salama, Guatemala. Interpreters were available for translation to the patients’ native dialect, to assist participants during their visit. We performed a genome-wide association study for ocular disease association on the blood samples using Illumina’s HumanOmni2.5-8 chip to examine single nucleotide polymorphism SNPs in this population. After implementing quality control measures, we performed adjusted logistic regression analysis to determine which genetic and epidemiological factors were associated with eye disease. We found that the most prevalent eye conditions were cataracts (54.8%) followed by pseudoexfoliation syndrome (PXF) (24.6%). The population with both conditions was 22.2%. In our epidemiological analysis, we found that eye disease was significantly associated with advanced age. Cataracts were significantly more common among those living in the 10 districts with the least resources. Furthermore, having cataracts was associated with a greater likelihood of PXF after adjusting for both age and sex. In our genetic analysis, the SNP most nominally significantly associated with PXF lay within the gene KSR2 (p < 1 × 10⁻⁵). Several SNPs were associated with cataracts at genome-wide significance after adjusting for covariates (p < 5 × 10⁻⁸). About seventy five percent of the 33 cataract-associated SNPs lie within 13 genes, with the majority of genes having only one significant SNP (5 × 10⁻⁸). Using bioinformatic tools including PhenGenI, the Ensembl genome browser and literature review, these SNPs and genes have not previously been associated with PXF or cataracts, separately or in combination. This study can aid in understanding the prevalence of eye conditions in this population to better help inform public health planning and the delivery of quality, accessible, and relevant health and preventative care within Salama, Guatemala.

Systemic Disease and Ocular Comorbidity Analysis of Geographically Isolated Federally Recognized American Indian Tribes of the Intermountain West

BACKGROUND

The American Indian Navajo and Goshute peoples are underserved patient populations residing in the Four Corners area of the United States and Ibupah, Utah, respectively.

METHODS

We conducted a cross-sectional study of epidemiological factors and lipid biomarkers that may be associated with type II diabetes, hypertension and retinal manifestations in tribal and non-tribal members in the study areas (n = 146 participants). We performed multivariate analyses to determine which, if any, risk factors were unique at the tribal level. Fundus photos and epidemiological data through standardized questionnaires were collected. Blood samples were collected to analyze lipid biomarkers. Univariate analyses were conducted and statistically significant factors at p < 0.10 were entered into a multivariate regression.

RESULTS

Of 51 participants for whom phenotyping was available, from the Four Corners region, 31 had type II diabetes (DM), 26 had hypertension and 6 had diabetic retinopathy (DR). Of the 64 participants from Ibupah with phenotyping available, 20 had diabetes, 19 had hypertension and 6 had DR. Navajo participants were less likely to have any type of retinopathy as compared to Goshute participants (odds ratio (OR) = 0.059; 95% confidence interval (CI) = 0.016-0.223; p < 0.001). Associations were found between diabetes and hypertension in both populations. Older age was associated with hypertension in the Four Corners, and the Navajo that reside there on the reservation, but not within the Goshute and Ibupah populations. Combining both the Ibupah, Utah and Four Corners study populations, being American Indian (p = 0.022), residing in the Four Corners (p = 0.027) and having hypertension (p < 0.001) increased the risk of DM. DM (p < 0.001) and age (p = 0.002) were significantly associated with hypertension in both populations examined. When retinopathy was evaluated for both populations combined, hypertension (p = 0.037) and living in Ibupah (p < 0.001) were associated with greater risk of retinopathy. When combining both American Indian populations from the Four Corners and Ibupah, those with hypertension were more likely to have DM (p < 0.001). No lipid biomarkers were found to be significantly associated with any disease state.

CONCLUSIONS

We found different comorbid factors with retinal disease outcome between the two tribes that reside within the Intermountain West. This is indicated by the association of tribe and with the type of retinopathy outcome when we combined the populations of American Indians. Overall, the Navajo peoples and the Four Corners had a higher prevalence of chronic disease that included diabetes and hypertension than the Goshutes and Ibupah. To the best of our knowledge, this is the first study to conduct an analysis for disease outcomes exclusively including the Navajo and Goshute tribe of the Intermountain West.

Model of genetic and environmental factors associated with type 2 diabetes mellitus in a Chinese Han population

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a metabolic disorder which accounts for high morbidity and mortality due to complications like renal failure, amputations, cardiovascular disease, and cerebrovascular events.

METHODS

We collected medical reports, lifestyle details, and blood samples of individuals and used the polymerase chain reaction-ligase detection reaction method to genotype the SNPs, and a visit was conducted in August 2016 to obtain the incidence of Type 2 diabetes in the 2113 eligible people. To explore which genes and environmental factors are associated with type 2 diabetes mellitus in a Chinese Han population, we used elastic net to build a model, which is to explain which variables are strongly associated with T2DM, rather than predict the occurrence of T2DM.

RESULT

The genotype of the additive of rs964184, together with the history of hypertension, regular intake of meat and waist circumference, increased the risk of T2DM (adjusted OR = 2.38, p = 0.042; adjusted OR = 3.31, p < 0.001; adjusted OR = 1.05, p < 0.001). The TT genotype of the additive and recessive models of rs12654264, the CC genotype of the additive and dominant models of rs2065412, the TT genotype of the additive and dominant models of rs4149336, together with the degree of education, regular exercise, reduced the risk of T2DM (adjusted OR = 0.46, p = 0.017; adjusted OR = 0.53, p = 0.021; adjusted OR = 0.59, p = 0.021; adjusted OR = 0.57, p = 0.01; adjusted OR = 0.59, p = 0.021; adjusted OR = 0.57, p = 0.01; adjusted OR = 0.50, p = 0.007; adjusted OR = 0.80, p = 0.032) .

CONCLUSION

Eventually we identified a set of SNPs and environmental factors: rs5805 in the SLC12A3, rs12654264 in the HMGCR, rs2065412 and rs414936 in the ABCA1, rs96418 in the ZPR1 gene, waistline, degree of education, exercise frequency, hypertension, and the intake of meat. Although there was no interaction between these variables, people with two risk factors had a higher risk of T2DM than those only having one factor. These results provide the theoretical basis for gene and other risk factors screening to prevent T2DM.

Genetics of diabetes mellitus and diabetes complications

Diabetes is one of the fastest growing diseases worldwide, projected to affect 693 million adults by 2045. Devastating macrovascular complications (cardiovascular disease) and microvascular complications (such as diabetic kidney disease, diabetic retinopathy and neuropathy) lead to increased mortality, blindness, kidney failure and an overall decreased quality of life in individuals with diabetes. Clinical risk factors and glycaemic control alone cannot predict the development of vascular complications; numerous genetic studies have demonstrated a clear genetic component to both diabetes and its complications. Early research aimed at identifying genetic determinants of diabetes complications relied on familial linkage analysis suited to strong-effect loci, candidate gene studies prone to false positives, and underpowered genome-wide association studies limited by sample size. The explosion of new genomic datasets, both in terms of biobanks and aggregation of worldwide cohorts, has more than doubled the number of genetic discoveries for both diabetes and diabetes complications. We focus herein on genetic discoveries for diabetes and diabetes complications, empowered primarily through genome-wide association studies, and emphasize the gaps in research for taking genomic discovery to the next level.

The derived allele of a novel intergenic variant at chromosome 11 associates with lower body mass index and a favorable metabolic phenotype in Greenlanders

The genetic architecture of the small and isolated Greenlandic population is advantageous for identification of novel genetic variants associated with cardio-metabolic traits. We aimed to identify genetic loci associated with body mass index (BMI), to expand the knowledge of the genetic and biological mechanisms underlying obesity. Stage 1 BMI-association analyses were performed in 4,626 Greenlanders. Stage 2 replication and meta-analysis were performed in additional cohorts comprising 1,058 Yup'ik Alaska Native people, and 1,529 Greenlanders. Obesity-related traits were assessed in the stage 1 study population. We identified a common variant on chromosome 11, rs4936356, where the derived G-allele had a frequency of 24% in the stage 1 study population. The derived allele was genome-wide significantly associated with lower BMI (beta (SE), -0.14 SD (0.03), p = 3.2x10-8), corresponding to 0.64 kg/m2 lower BMI per G allele in the stage 1 study population. We observed a similar effect in the Yup'ik cohort (-0.09 SD, p = 0.038), and a non-significant effect in the same direction in the independent Greenlandic stage 2 cohort (-0.03 SD, p = 0.514). The association remained genome-wide significant in meta-analysis of the Arctic cohorts (-0.10 SD (0.02), p = 4.7x10-8). Moreover, the variant was associated with a leaner body type (weight, -1.68 (0.37) kg; waist circumference, -1.52 (0.33) cm; hip circumference, -0.85 (0.24) cm; lean mass, -0.84 (0.19) kg; fat mass and percent, -1.66 (0.33) kg and -1.39 (0.27) %; visceral adipose tissue, -0.30 (0.07) cm; subcutaneous adipose tissue, -0.16 (0.05) cm, all p<0.0002), lower insulin resistance (HOMA-IR, -0.12 (0.04), p = 0.00021), and favorable lipid levels (triglyceride, -0.05 (0.02) mmol/l, p = 0.025; HDL-cholesterol, 0.04 (0.01) mmol/l, p = 0.0015). In conclusion, we identified a novel variant, where the derived G-allele possibly associated with lower BMI in Arctic populations, and as a consequence also leaner body type, lower insulin resistance, and a favorable lipid profile.

Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome

Schizophrenia (SCZ) and major depressive disorder (MDD) in treatment-naive patients are associated with increased risk for type 2 diabetes (T2D) and metabolic syndrome (MetS). SCZ, MDD, T2D, and MetS are often comorbid and their comorbidity increases cardiovascular risk: Some risk genes are likely co-shared by them. For instance, transcription factor 7-like 2 (TCF7L2) and proteasome 26S subunit, non-ATPase 9 (PSMD9) are two genes independently reported as contributing to T2D and SCZ, and PSMD9 to MDD as well. However, there are scarce data on the shared genetic risk among SCZ, MDD, T2D, and/or MetS. Here, we briefly describe T2D, MetS, SCZ, and MDD and their genetic architecture. Next, we report separately about the comorbidity of SCZ and MDD with T2D and MetS, and their respective genetic overlap. We propose a novel hypothesis that genes of the prolactin (PRL)-pathway may be implicated in the comorbidity of these disorders. The inherited predisposition of patients with SCZ and MDD to psychoneuroendocrine dysfunction may confer increased risk of T2D and MetS. We illustrate a strategy to identify risk variants in each disorder and in their comorbid psychoneuroendocrine and mental-metabolic dysfunctions, advocating for studies of genetically homogeneous and phenotype-rich families. The results will guide future studies of the shared predisposition and molecular genetics of new homogeneous endophenotypes of SCZ, MDD, and metabolic impairment.

Genetics of metabolic traits in Greenlanders: lessons from an isolated population

In this review, we describe the extraordinary population of Greenland, which differs from large outbred populations of Europe and Asia, both in terms of population history and living conditions. Many years in isolation, small population size and an extreme environment have shaped the genetic composition of the Greenlandic population. The unique genetic background combined with the transition from a traditional Inuit lifestyle and diet, to a more Westernized lifestyle, has led to an increase in the prevalence of metabolic conditions like obesity, where the prevalence from 1993 to 2010 has increased from 16.4% to 19.4% among men, and from 13.0% to 25.4% among women, type 2 diabetes and cardiovascular diseases. The genetic susceptibility to metabolic conditions has been explored in Greenlanders, as well as other isolated populations, taking advantage of population-genetic properties of these populations. During the last 10 years, these studies have provided examples of loci showing evidence of positive selection, due to adaption to Arctic climate and Inuit diet, including TBC1D4 and FADS/CPT1A, and have facilitated the discovery of several loci associated with metabolic phenotypes. Most recently, the c.2433-1G>A loss-of-function variant in ADCY3 associated with obesity and type 2 diabetes was described. This locus has provided novel biological insights, as it has been shown that reduced ADCY3 function causes obesity through disrupted function in primary cilia. Future studies of isolated populations will likely provide further genetic as well as biological insights.

High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes

Type 2 diabetes (T2D) is a complex disorder that is caused by a combination of genetic, epigenetic, and environmental factors. High-throughput approaches have opened a new avenue toward a better understanding of the molecular bases of T2D. A genome-wide association studies (GWASs) identified a group of the most common susceptibility genes for T2D (i.e., TCF7L2, PPARG, KCNJ1, HNF1A, PTPN1, and CDKAL1) and illuminated novel disease-causing pathways. Next-generation sequencing (NGS)-based techniques have shed light on rare-coding genetic variants that account for an appreciable fraction of T2D heritability (KCNQ1 and ADRA2A) and population risk of T2D (SLC16A11, TPCN2, PAM, and CCND2). Moreover, single-cell sequencing of human pancreatic islets identified gene signatures that are exclusive to α-cells (GCG, IRX2, and IGFBP2) and β-cells (INS, ADCYAP1, INS-IGF2, and MAFA). Ongoing epigenome-wide association studies (EWASs) have progressively defined links between epigenetic markers and the transcriptional activity of T2D target genes. Differentially methylated regions were found in TCF7L2, THADA, KCNQ1, TXNIP, SOCS3, SREBF1, and KLF14 loci that are related to T2D. Additionally, chromatin state maps in pancreatic islets were provided and several non-coding RNAs (ncRNA) that are key to T2D pathogenesis were identified (i.e., miR-375). The present review summarizes major progress that has been made in mapping the (epi)genomic landscape of T2D within the last few years.

Genomic insights into the causes of type 2 diabetes

Genome-wide association studies have implicated around 250 genomic regions in predisposition to type 2 diabetes, with evidence for causal variants and genes emerging for several of these regions. Understanding of the underlying mechanisms, including the interplay between β-cell failure, insulin sensitivity, appetite regulation, and adipose storage has been facilitated by the integration of multidimensional data for diabetes-related intermediate phenotypes, detailed genomic annotations, functional experiments, and now multiomic molecular features. Studies in diverse ethnic groups and examples from population isolates have shown the value and need for a broad genomic approach to this global disease. Transethnic discovery efforts and large-scale biobanks in diverse populations and ancestries could help to address some of the Eurocentric bias. Despite rapid progress in the discovery of the highly polygenic architecture of type 2 diabetes, dominated by common alleles with small, cumulative effects on disease risk, these insights have been of little clinical use in terms of disease prediction or prevention, and have made only small contributions to subtype classification or stratified approaches to treatment. Successful development of academia-industry partnerships for exome or genome sequencing in large biobanks could help to deliver economies of scale, with implications for the future of genomics-focused research.

Birth weight and type 2 diabetes: A meta-analysis

The prevalence of T2DM is increasing around the world on a yearly basis. A meta-analysis was conducted to analyze the association between birth weight and incidence of type 2 diabetes mellitus (T2DM). A literature search was performed from January 1990 to June 2016 in PubMed, ScienceDirect, SpringerLink, China National Knowledge Infrastructure and Chinese Biomedical Literature Database. After reviewing characteristics of all the included studies systematically, a meta-analytical method was employed to calculate the pooled odds ratios (ORs) and associated 95% confidence intervals (CI) from random-effects models. Heterogeneity was assessed by Q-statistic test. Funnel plot, Begg's and Egger's linear regression tests were applied to evaluate publication bias. A sensitivity analysis was also performed to assess the robustness of results. According to inclusion and exclusion criteria, 8 studies were selected to be included in the meta-analysis. Compared with normal birth weight (2,500–4,000 g), low birth weight (<2,500 g) was associated with an increased risk of T2DM (OR, 1.55; 95% CI, 1.39–1.73; P<0.001). No significant difference was observed between high birth weight (>4,000 g) and normal birth weight in terms of the risk of T2DM (OR, 0.98; 95% CI, 0.79–1.22). Compared with high birth weight, low birth weight was associated with an increased risk of diabetes mellitus (OR, 1.58; 95% CI, 1.30–1.93; P<0.001). These findings indicated that there may be an inverse linear association between birth weight and T2DM.

Prioritising Causal Genes at Type 2 Diabetes Risk Loci

PURPOSE OF REVIEW

Genome-wide association studies (GWAS) for type 2 diabetes (T2D) risk have identified a large number of genetic loci associated with disease susceptibility. However, progress moving from association signals through causal genes to functional understanding has so far been slow, hindering clinical translation. This review discusses the benefits and limitations of emerging, unbiased approaches for prioritising causal genes at T2D risk loci.

RECENT FINDINGS

Candidate causal genes can be identified by a number of different strategies that rely on genetic data, genomic annotations, and functional screening of selected genes. To overcome the limitations of each particular method, integration of multiple data sets is proving essential for establishing confidence in the prioritised genes. Previous studies have also highlighted the need to support these efforts through identification of causal variants and disease-relevant tissues. Prioritisation of causal genes at T2D risk loci by integrating complementary lines of evidence promises to accelerate our understanding of disease pathology and promote translation into new therapeutics.

Genetics of early-onset Parkinson's disease in Finland: exome sequencing and genome-wide association study

Several genes and risk factors are associated with Parkinson's disease (PD). Although many of the genetic markers belong to a common pathway, a unifying pathogenetic mechanism is yet to be found. Also, missing heritability analyses have estimated that only part of the genetic influence contributing to PD has been found. Here, we carried out whole-exome sequencing (WES) on 438 Finnish patients with early-onset PD. We also reanalyzed previous data from genome-wide association studies (GWAS) on the same cohort. Variants in the CEL gene/locus were associated with PD in both GWAS and WES analysis. Exome-wide gene-based association tests also identified the MPHOSPH10, TAS2R19, and SERPINA1 genes in the discovery data set (p < 2.5E-6). MPHOSPH10 had estimated odds ratio (OR) of 1.53, and the rs141620200 variant in SERPINA1 had OR of 1.27. We identified several candidate genes, but further investigation is required to determine the role of these genes in PD.

Gene expression signature: a powerful approach for drug discovery in diabetes

Type 2 diabetes (T2D) is increasing in prevalence at an alarming rate around the world. Much effort has gone into the discovery and design of antidiabetic drugs; however, those already available are unable to combat the underlying causes of the disease and instead only moderate the symptoms. The reason for this is that T2D is a complex disease, and attempts to target one biological pathway are insufficient to combat the full extent of the disease. Additionally, the underlying pathophysiology of this disease is yet to be fully elucidated making it difficult to design drugs that target the mechanisms involved. Therefore, the approach of designing new drugs aimed at a specific molecular target is not optimal and a more expansive, unbiased approach is required. In this review, we will look at the current state of diabetes treatments and how these target the disease symptoms but are unable to combat the underlying causes. We will also review how the technique of gene expression signatures (GESs) has been used successfully for other complex diseases and how this may be applied as a powerful tool for the discovery of new drugs for T2D.