Promises and Challenges of populational Proteomics in Health and Disease.

Advances in proteomic assay technologies have significantly increased coverage and throughput, enabling recent increases in the number of large-scale population-based proteomic studies of human plasma and serum. Improvements in multiplexed protein assays have facilitated the quantification of thousands of proteins over a large dynamic range, a key requirement for detecting the lowest-ranging, and potentially the most disease-relevant, blood-circulating proteins. In this perspective, we examine how populational proteomic datasets in conjunction with other concurrent omic measures can be leveraged to better understand the genomic and non-genomic correlates of the soluble proteome, constructing biomarker panels for disease prediction, among others. Mass spectrometry workflows are discussed as they are becoming increasingly competitive with affinity-based array platforms in terms of speed, cost, and proteome coverage due to advances in both instrumentation and workflows. Despite much success, there remain considerable challenges such as orthogonal validation and absolute quantification. We also highlight emergent challenges associated with study design, analytical considerations, and data integration as population-scale studies are run in batches and may involve longitudinal samples collated over many years. Lastly, we take a look at the future of what the nascent next-generation proteomic technologies might provide to the analysis of large sets of blood samples, as well as the difficulties in designing large-scale studies that will likely require participation from multiple and complex funding sources and where data sharing, study designs, and financing must be solved.

Multi-trait analysis of gene-by-environment interactions in large-scale genetic studies.

Identifying genotype-by-environment interaction (GEI) is challenging because the GEI analysis generally has low power. Large-scale consortium-based studies are ultimately needed to achieve adequate power for identifying GEI. We introduce Multi-Trait Analysis of Gene-Environment Interactions (MTAGEI), a powerful, robust, and computationally efficient framework to test gene-environment interactions on multiple traits in large data sets, such as the UK Biobank (UKB). To facilitate the meta-analysis of GEI studies in a consortium, MTAGEI efficiently generates summary statistics of genetic associations for multiple traits under different environmental conditions and integrates the summary statistics for GEI analysis. MTAGEI enhances the power of GEI analysis by aggregating GEI signals across multiple traits and variants that would otherwise be difficult to detect individually. MTAGEI achieves robustness by combining complementary tests under a wide spectrum of genetic architectures. We demonstrate the advantages of MTAGEI over existing single-trait-based GEI tests through extensive simulation studies and the analysis of the whole exome sequencing data from the UKB.

Rare variant association on unrelated individuals in case-control studies using aggregation tests: existing methods and current limitations.

Over the past years, progress made in next-generation sequencing technologies and bioinformatics have sparked a surge in association studies. Especially, genome-wide association studies (GWASs) have demonstrated their effectiveness in identifying disease associations with common genetic variants. Yet, rare variants can contribute to additional disease risk or trait heterogeneity. Because GWASs are underpowered for detecting association with such variants, numerous statistical methods have been recently proposed. Aggregation tests collapse multiple rare variants within a genetic region (e.g. gene, gene set, genomic loci) to test for association. An increasing number of studies using such methods successfully identified trait-associated rare variants and led to a better understanding of the underlying disease mechanism. In this review, we compare existing aggregation tests, their statistical features and scope of application, splitting them into the five classical classes: burden, adaptive burden, variance-component, omnibus and other. Finally, we describe some limitations of current aggregation tests, highlighting potential direction for further investigations.

Rare variant association analyses reveal the significant contribution of carbohydrate metabolic disturbance in severe adolescent idiopathic scoliosis.

BACKGROUND: Adolescent idiopathic scoliosis (AIS), the predominant genetic-influenced scoliosis, results in spinal deformities without vertebral malformations. However, the molecular aetiology of AIS remains unclear. METHODS: Using genome/exome sequencing, we studied 368 patients with severe AIS (Cobb angle >40°) and 3794 controls from a Han Chinese cohort. We performed gene-based and pathway-based weighted rare variant association tests to assess the mutational burden of genes and established biological pathways. Differential expression analysis of muscle tissues from 14 patients with AIS and 15 controls was served for validation. RESULTS: SLC16A8, a lactate transporter linked to retinal glucose metabolism, was identified as a novel severe AIS-associated gene (p=3.08E-06, false discovery rate=0.009). Most AIS cases with deleterious SLC16A8 variants demonstrated early onset high myopia preceding scoliosis. Pathway-based burden test also revealed a significant enrichment in multiple carbohydrate metabolism pathways, especially galactose metabolism. Patients with deleterious variants in these genes demonstrated a significantly larger spinal curve. Genes related to catabolic processes and nutrient response showed divergent expression between AIS cases and controls, reinforcing our genomic findings. CONCLUSION: This study uncovers the pivotal role of genetic variants in carbohydrate metabolism in the development of AIS, unveiling new insights into its aetiology and potential treatment.

Functional annotation with expression validation identifies novel metastasis-relevant genes from post-GWAS risk loci in sporadic colorectal carcinomas.

BACKGROUND: Colorectal cancer (CRC) is the third highest incidence cancer and is the leading cause of cancer mortality worldwide. Metastasis to distal organ is the major cause of cancer mortality. However, the underlying genetic factors are unclear. This study aimed to identify metastasis-relevant genes and pathways for better management of metastasis-prone patients. METHODS: A case-case genome-wide association study comprising 2677 sporadic Chinese CRC cases (1282 metastasis-positive vs 1395 metastasis-negative) was performed using the Human SNP6 microarray platform and analysed with the correlation/trend test based on the additive model. SNP variants with association testing -log10 p value ≥5 were imported into Functional Mapping and Annotation (FUMA) for functional annotation. RESULTS: Glycolysis was uncovered as the top hallmark gene set. Transcripts from two of the five genes profiled, hematopoietic substrate 1 associated protein X 1 (HAX1) and hyaluronan-mediatedmotility receptor (HMMR), were significantly upregulated in the metastasis-positive tumours. In contrast to disease-risk variants, HAX1 appeared to act synergistically with HMMR in significantly impacting metastasis-free survival. Examining the subtype datasets with FUMA and Ingenuity Pathway Analysis (IPA) identified distinct pathways demonstrating sexual dimorphism in CRC metastasis. CONCLUSIONS: Combining genome-wide association testing with in silico functional annotation and wet-bench validation identified metastasis-relevant genes that could serve as features to develop subtype-specific metastasis-risk signatures for tailored management of patients with stage I-III CRC.

Joint analysis of multiple phenotypes for extremely unbalanced case-control association studies.

In genome-wide association studies (GWAS) for thousands of phenotypes in biobanks, most binary phenotypes have substantially fewer cases than controls. Many widely used approaches for joint analysis of multiple phenotypes produce inflated type I error rates for such extremely unbalanced case-control phenotypes. In this research, we develop a method to jointly analyze multiple unbalanced case-control phenotypes to circumvent this issue. We first group multiple phenotypes into different clusters based on a hierarchical clustering method, then we merge phenotypes in each cluster into a single phenotype. In each cluster, we use the saddlepoint approximation to estimate the p value of an association test between the merged phenotype and a single nucleotide polymorphism (SNP) which eliminates the issue of inflated type I error rate of the test for extremely unbalanced case-control phenotypes. Finally, we use the Cauchy combination method to obtain an integrated p value for all clusters to test the association between multiple phenotypes and a SNP. We use extensive simulation studies to evaluate the performance of the proposed approach. The results show that the proposed approach can control type I error rate very well and is more powerful than other available methods. We also apply the proposed approach to phenotypes in category IX (diseases of the circulatory system) in the UK Biobank. We find that the proposed approach can identify more significant SNPs than the other viable methods we compared with.

Fine Particulate Matter Exposure, Genetic Susceptibility, and the Risk of Incident Stroke: A Prospective Cohort Study.

BACKGROUND: Both genetic factors and environmental air pollution contribute to the risk of stroke. However, it is unknown whether the association between air pollution and stroke risk is influenced by the genetic susceptibilities of stroke and its risk factors. METHODS: This prospective cohort study included 40 827 Chinese adults without stroke history. Satellite-based monthly fine particulate matter (PM2.5) estimation at 1-km resolution was used for exposure assessment. Based on 534 identified genetic variants from genome-wide association studies in East Asians, we constructed 6 polygenic risk scores for stroke and its risk factors, including atrial fibrillation, blood pressure, type 2 diabetes, body mass index, and triglyceride. The Cox proportional hazards model was applied to evaluate the hazard ratios and 95% CIs for the associations of PM2.5 and polygenic risk score with incident stroke and the potential effect modifications. RESULTS: Over a median follow-up of 12.06 years, 3147 incident stroke cases were documented. Compared with the lowest quartile of PM2.5 exposure, the hazard ratio (95% CI) for stroke in the highest quartile group was 2.72 (2.42-3.06). Among individuals at high genetic risk, the relative risk of stroke was 57% (1.57; 1.40-1.76) higher than those at low genetic risk. Although no statistically significant interaction was found, participants with both the highest PM2.5 and high genetic risk showed the highest risk of stroke, with ≈4× that of the lowest PM2.5 and low genetic risk group (hazard ratio, 3.55 [95% CI, 2.84-4.44]). Similar upward gradients were observed in the risk of stroke when assessing the joint effects of PM2.5 and genetic risks of blood pressure, type 2 diabetes, body mass index, atrial fibrillation, and triglyceride. CONCLUSIONS: Long-term exposure to PM2.5 was associated with a higher risk of incident stroke across different genetic susceptibilities. Our findings highlighted the great importance of comprehensive assessment of air pollution and genetic risk in the prevention of stroke.

Diagnosing Monogenic Stroke at Younger Age.

BACKGROUND: An increasing number of monogenic conditions underlying stroke are being identified. We explored the possibilities of increasing the diagnostic yield of monogenic stroke in a population under 56 years of age. METHODS: Fifty probands ≤55 years at their first stroke episode were characterized clinically and investigated by whole genome sequencing. Probands had one or more of: (1) one or more first to second degree relatives with stroke under 60 years or same stroke-causing condition/disease; (2) no hypertension, hypercholesterolemia, diabetes, heart disease, or smoking; or (3) either multiple stroke episodes or multiple arterial dissections. Variants with minor allele frequency under 0.01, identified by using our stroke gene panels, were assessed. The stroke subtypes, including large artery atherosclerotic, large artery nonatherosclerotic (tortuosity, dolichoectasia, aneurysm, nonatherosclerotic dissection, or occlusion), cerebral small vessel disease, cardioembolic (arrhythmia, heart defect, or cardiomyopathy), coagulation dysfunctions (venous thrombosis, arterial thrombosis, or bleeding tendency), intracerebral hemorrhage, vascular malformations (cavernoma or arteriovenous malformations), metabolic disorders, or cryptogenic embolic, were used for genotype-phenotype correlation. In a final step, we combined genetic and clinical information to determine if the genetic variant likely was the cause of stroke in the patients. RESULTS: Whole genome sequencing of younger patients with stroke identified 17 clinically matching genetic variants in 15 of 50 (30%) patients, while a stronger clinical correlation with stroke was established in only 6 (12%) of them. Stroke-related genetic variants were identified in 4 of 5 (80%) patients with cardioembolic stroke subtype, 3 of 4 (75%) with intracerebral hemorrhage, 7 of 18 (39%) with cryptogenic embolic stroke, 1 of 6 (17%) with small vessel disease, and 3 of 15 (20%) of patients with nonatherosclerotic large artery stroke, including 1 of 11 (9%) with cervical dissection stroke. CONCLUSIONS: Careful clinical interpretation of whole genome data using stroke gene panels can detect monogenic causes of early stroke, allowing individualized follow-up and opening new possibilities for potential treatment.

Phenotypic variability in Joubert syndrome is partially explained by ciliary pathophysiology.

INTRODUCTION: Joubert syndrome (JS) arises from defects of primary cilia resulting in potential malformations of the brain, kidneys, eyes, liver, and limbs. Several of the 35+ genes associated with JS have recognized genotype/phenotype correlations, but most genes have not had enough reported individuals to draw meaningful conclusions. METHODS: A PubMed literature review identified 688 individuals with JS across 32 genes and 112 publications to bolster known genotype/phenotype relationships and identify new correlations. All included patients had the "molar tooth sign" and a confirmed genetic diagnosis. Individuals were categorized by age, ethnicity, sex and the presence of developmental disability/intellectual disability, hypotonia, abnormal eye movements, ataxia, visual impairment, renal impairment, polydactyly, and liver abnormalities. RESULTS: Most genes demonstrated unique phenotypic profiles. Grouping proteins based on physiologic interactions established stronger phenotypic relationships that reflect known ciliary pathophysiology. Age-stratified data demonstrated that end-organ disease is progressive in JS. Most genes demonstrated a significant skew towards having variants with either residual protein function or no residual protein function. CONCLUSION: This cohort demonstrates that clinically meaningful genotype/phenotype relationships exist within most JS-related genes and can be referenced to allow for more personalized clinical care.

Participation of lncRNAs in the development of diabetic complications: Systematic review and meta-analysis. I. Rat.

AIMS: We evaluated the involvement of lncRNAs in the development of pathologies associated with chronic hyperglycaemia in rat models in a model of type 1, type 2 and gestational diabetes. METHODS: Reports were searched in Dialnet, Scielo, HINARI, Springer, ClinicalKey, OTseeker, PubMed and different grey literature databases with any restrictions. Bibliography databases will be searched from their inception to December 2022. RESULTS: Thirty-seven studies met our criteria, and they had the following characteristics: original experimental studies on diabetes, the lncRNAs were extracted or measured from tissues of specific areas and the results were expressed in terms of standard measures by RT-PCR. In most studies, both primary and secondary outcomes were mentioned. On the other hand, we found a total of nine diabetic complications, being retinopathy, nephropathy and neuropathy the most representatives. Additionally, it was found that MALAT1, H19, NEAT1 and TUG1 are the most studied lncRNAs about these complications in rats. On the other hand, the lncRNAs with the highest rate of change were MSTRG.1662 (17.85; 13.78, 21.93), ENSRNOT00000093120_Aox3 (7.13; 5.95, 8.31) and NONRATG013497.2 (-5.55; -7.18, -3.93). CONCLUSIONS: This review found a significant involvement of lncRNAs in the progression of pathologies associated with chronic hyperglycaemia in rat models, and further studies are needed to establish their potential as biomarkers and therapeutic targets for diabetes.

Additive Effect of APOE Rare Variants on the Phenotype of Familial Hypercholesterolemia.

BACKGROUND: Autosomal dominant hypercholesterolemia (ADH) is due to deleterious variants in LDLR, APOB, or PCSK9 genes. Double heterozygote for these genes induces a more severe phenotype. More recently, a new causative variant of heterozygous ADH was identified in APOE. Here we study the phenotype of 21 adult patients, double heterozygotes for rare LDLR and rare APOE variants (LDLR+APOE) in a national wide French cohort. METHODS: LDLR, APOB, PCSK9, and APOE genes were sequenced in 5743 probands addressed for ADH genotyping. The lipid profile and occurrence of premature atherosclerotic cardiovascular diseases were compared between the LDLR+APOE carriers (n=21) and the carriers of the same LDLR causative variants alone (n=22). RESULTS: The prevalence of LDLR+APOE carriers in this French ADH cohort is 0.4%. Overall, LDL (low-density lipoprotein)-cholesterol concentrations were 23% higher in LDLR+APOE patients than in LDLR patients (9.14±2.51 versus 7.43±1.59 mmol/L, P=0.0221). When only deleterious or probably deleterious variants were considered, the LDL-cholesterol concentrations were 46% higher in LDLR+APOE carriers than in LDLR carriers (10.83±3.45 versus 7.43±1.59 mmol/L, P=0.0270). Two patients exhibited a homozygous familial hypercholesterolemia phenotype (LDL-cholesterol >13 mmol/L). Premature atherosclerotic cardiovascular disease was more common in LDLR+APOE patients than in LDLR carriers (70% versus 30%, P=0.026). CONCLUSIONS: Although an incomplete penetrance should be taken into account for APOE variant classification, these results suggest an additive effect of deleterious APOE variants on ADH phenotype highlighting the relevance of APOE sequencing.

Characterising heart rhythm abnormalities associated with Xp22.31 deletion.

BACKGROUND: Genetic deletions at Xp22.31 are associated with the skin condition X linked ichthyosis (XLI), and with a substantially increased risk of atrial fibrillation/flutter (AF), in males. AF is associated with elevated thrombosis, heart failure, stroke and dementia risk. METHODS: Through: (a) examining deletion carriers with a diagnosis of AF in UK Biobank, (b) undertaking an online survey regarding abnormal heart rhythms (AHRs) in men/boys with XLI and female carriers of XLI-associated deletions and (c) screening for association between common genetic variants within Xp22.31 and idiopathic AF-related conditions in UK Biobank, we have investigated how AHRs manifest in deletion carriers, and have identified associated risk factors/comorbidities and candidate gene(s). Finally, we examined attitudes towards heart screening in deletion carriers. RESULTS: We show that AHRs may affect up to 35% of deletion carriers (compared with <20% of age-matched non-carriers), show no consistent pattern of onset but may be precipitated by stress, and typically resolve quickly and respond well to intervention. Gastrointestinal (GI) conditions and asthma/anaemia were the most strongly associated comorbidities in male and female deletion carriers with AHR, respectively. Genetic analysis indicated significant enrichment of common AF risk variants around STS (7 065 298-7 272 682 bp in GRCh37/hg19 genome build) in males, and of common GI disorder and asthma/anaemia risk variants around PNPLA4 (7 866 804-7 895 780 bp) in males and females, respectively. Deletion carriers were overwhelmingly in favour of cardiac screening implementation. CONCLUSION: Our data suggest AHRs are frequently associated with Xp22.31 deletion, and highlight subgroups of deletion carriers that may be prioritised for screening. Examining cardiac function further in deletion carriers, and in model systems lacking steroid sulfatase, may clarify AF pathophysiology.

Single amino acid variation in MAB21L1 is dominantly associated with congenital eye defects.

BACKGROUND: Diagnosis of a genetic disease and determination of the causative molecular lesion rely on the availability of the disease-associated pedigrees. Microphthalmia is a congenital eye defect due to an insufficiently developed visual system; its prevalence is 1-3 in 10 000 live births. OBJECTIVE: We analysed a pedigree exhibiting autosomal dominant inheritance of microphthalmia to determine the genetic lesion; used AlphaFold2 to predict the changes in the protein's 3-Dimensional structure; and compared wild-type and variant proteins in cultured cells or Drosophila model was used to explore the cellular or developmental function of the encoded product. RESULTS: We identified a novel missense variation, F52L, in MAB21L1 that is absent in population databases and present exclusively in the individuals diagnosed with microphthalmia in this pedigree. Common structural changes were predicted for the disease-associated variants clustered at amino acids 49-52, and these variant products were also predominantly trapped in the cytoplasm of cultured human lens epithelia. To recapitulate its dominant effect in development, we expressed the Drosophila homologue corresponding to MAB21L1F52L and caused malformation of sensory organs. CONCLUSION: Mutations at the residues 49-52 of MAB21L1 compromise eye development. We recommend including MAB21L1 in the genetic testing panel for congenital eye disorders.

Ability of a polygenic risk score to refine colorectal cancer risk in Lynch syndrome.

BACKGROUND: Polygenic risk scores (PRSs) have been used to stratify colorectal cancer (CRC) risk in the general population, whereas its role in Lynch syndrome (LS), the most common type of hereditary CRC, is still conflicting. We aimed to assess the ability of PRS to refine CRC risk prediction in European-descendant individuals with LS. METHODS: 1465 individuals with LS (557 MLH1, 517 MSH2/EPCAM, 299 MSH6 and 92 PMS2) and 5656 CRC-free population-based controls from two independent cohorts were included. A 91-SNP PRS was applied. A Cox proportional hazard regression model with 'family' as a random effect and a logistic regression analysis, followed by a meta-analysis combining both cohorts were conducted. RESULTS: Overall, we did not observe a statistically significant association between PRS and CRC risk in the entire cohort. Nevertheless, PRS was significantly associated with a slightly increased risk of CRC or advanced adenoma (AA), in those with CRC diagnosed <50 years and in individuals with multiple CRCs or AAs diagnosed <60 years. CONCLUSION: The PRS may slightly influence CRC risk in individuals with LS in particular in more extreme phenotypes such as early-onset disease. However, the study design and recruitment strategy strongly influence the results of PRS studies. A separate analysis by genes and its combination with other genetic and non-genetic risk factors will help refine its role as a risk modifier in LS.

Idiopathic Pulmonary Fibrosis Is Associated with Common Genetic Variants and Limited Rare Variants.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a rare, irreversible, and progressive disease of the lungs. Common genetic variants, in addition to nongenetic factors, have been consistently associated with IPF. Rare variants identified by candidate gene, family-based, and exome studies have also been reported to associate with IPF. However, the extent to which rare variants, genome-wide, may contribute to the risk of IPF remains unknown. Objectives: We used whole-genome sequencing to investigate the role of rare variants, genome-wide, on IPF risk. Methods: As part of the Trans-Omics for Precision Medicine Program, we sequenced 2,180 cases of IPF. Association testing focused on the aggregated effect of rare variants (minor allele frequency ⩽0.01) within genes or regions. We also identified individual rare variants that are influential within genes and estimated the heritability of IPF on the basis of rare and common variants. Measurements and Main Results: Rare variants in both TERT and RTEL1 were significantly associated with IPF. A single rare variant in each of the TERT and RTEL1 genes was found to consistently influence the aggregated test statistics. There was no significant evidence of association with other previously reported rare variants. The SNP heritability of IPF was estimated to be 32% (SE = 3%). Conclusions: Rare variants within the TERT and RTEL1 genes and well-established common variants have the largest contribution to IPF risk overall. Efforts in risk profiling or the development of therapies for IPF that focus on TERT, RTEL1, common variants, and environmental risk factors are likely to have the largest impact on this complex disease.

Polymorphisms in Innate and Adaptive Immune Genes in Subjects with Allergic Bronchopulmonary Aspergillosis Complicating Asthma.

Innate and adaptive immunity play a crucial role in allergic bronchopulmonary aspergillosis (ABPA) pathogenesis. We performed next-generation sequencing using the Illumina TruSight One panel (4,811 human disease-associated genes, at least 20 × coverage) and selected 22 known immune genes (toll-like receptors (TLRs), C-type lectin, interleukin-4 receptor, and others). We included ABPA (n = 18), asthma without ABPA (n = 12), and healthy controls (n = 8). We analyzed 3011 SNPs from 22 genes and identified 145 SNPs (13 genes) that were present only in the disease groups and absent in controls. The SNP frequency overall was significantly higher in ABPA than in asthmatics (89/145 [61.4%] vs. 56/145 [38.6%], p = 0.0001). The SNP frequency in the TLR10 gene was also significantly higher in ABPA than in asthma (p = 0.017). Association analysis further revealed three genes having significant associations. Of these, NOS3 and HLA-DQB1 are associated with antimicrobial activity and adaptive immunity. More extensive studies are required to confirm our findings.

Protective Effect of EBF Transcription Factor 1 (EBF1) Polymorphism in Sporadic and Familial Spontaneous Preterm Birth: Insights from a Case-Control Study.

This study investigated the potential role of specific single-nucleotide polymorphisms (SNPs) in the genes Astrotactin 1 (ASTN1), EBF Transcription Factor 1 (EBF1), Eukaryotic Elongation Factor, Selenocysteine-tRNA Specific (EEFSEC), Microtubule-Associated Serine/Threonine Kinase 1 (MAST1), and Tumor Necrosis Factor Alpha (TNF-α) to assess whether these genetic variants contribute to the risk of spontaneous preterm birth (sPTB). A case-control study was conducted involving 573 women from Croatia and Slovenia: 248 with sporadic sPTB (positive personal and negative family history of sPTB before 37 weeks' gestation), 44 with familial sPTB (positive personal and family history of sPTB before 37 weeks' gestation), and 281 control women. The analysis of ASTN1 rs146756455, EBF1 rs2963463, EBF1 rs2946169, EEFSEC rs201450565, MAST1 rs188343966, and TNF-α rs1800629 SNPs was performed using TaqMan real-time PCR. p-values were Bonferroni-adjusted for multiple comparisons. EBF1 SNP rs2963463 was significantly associated with sPTB (p adj = 0.03). Women carrying the CC genotype had a 3-4-times lower risk of sPTB (p adj < 0.0001). In addition, a significant difference in the frequency of the minor C allele was observed when comparing familial sPTB cases with controls (p adj < 0.0001). All other associations were based on unadjusted p-values. The minor T allele of EBF1 SNP rs2946169 was more frequent in sPTB cases overall than in controls, especially in sporadic sPTB (p = 0.045). Similarly, the CC genotype of ASTN1 SNP rs146756455 was more frequent in sporadic sPTB cases compared to controls (p = 0.019). Finally, the TNF-α SNP rs1800629 minor A allele and AA genotype were more common in the familial sPTB group compared to sporadic sPTB and controls (p < 0.05). The EBF1 SNP rs2963463 polymorphism showed a protective effect in the pathogenesis of sPTB, particularly in women carrying the CC genotype. Moreover, EBF1 SNP rs2946169 and ASTN1 SNP rs146756455, as well as TNF-α SNP rs1800629, were associated with an increased risk of sPTB, representing suggestive potential risk factors for sporadic and familial sPTB, respectively.

Genome-Wide Association study of susceptibility to respiratory syncytial virus hospitalization in young children < 5 years of age.

BACKGROUND: Worldwide, respiratory syncytial virus (RSV) infections are among the most common causes of infant hospitalization. Host genetic factors influencing the risk and severity of RSV infection are not well known. METHODS: We conducted a genome-wide association study (GWAS) to investigate single nucleotide polymorphisms (SNPs) associated with severe RSV infections using a nested case-control design based on two Danish cohorts. We compared SNPs from 1786 children hospitalized with RSV to 45,060 controls without a RSV-coded hospitalization. We performed gene-based testing, tissue-enrichment, gene-set enrichment, and a meta-analysis of the two cohorts. Finally, an analysis of potential associations between the severity of RSV infection and genetic markers was performed. RESULTS: We did not detect any significant genome-wide associations between SNPs and RSV infection, or the severity of RSV. We did find potential loci associated with RSV infections on chromosome 5 in one cohort, however, we failed to replicate any signals in both cohorts. CONCLUSION: Despite being the largest GWAS of severe RSV infection, we did not detect any genome-wide significant loci. This may be an indication of a lack of power, or an absence of signal. Future studies might include mild illness and need to be larger to detect any significant associations.

Pleiotropic Bias and Study Design Considerations in Genetic Association Studies.

Background: Case-control studies are efficient designs for investigating gene-disease associations. A discovery of genome-wide association studies (GWAS) is that many genetic variants are associated with multiple health outcomes and diseases, a phenomenon known as pleiotropy. We aimed to discuss about pleiotropic bias in genetic association studies. Methods: The opinions of the researchers on the basis of the literature were presented as a critical review. Results: Pleiotropic effect can bias the results of gene-disease association studies if they use individuals with pre-existing diseases as the control group, while the disease in cases and controls have shared genetic markers. The idea supports the conclusion that when the exposure of interest in a case-control study is a genetic marker, the use of controls from diseased cases that share similar genetic markers may increase the risk of pleiotropic effect. However, not manifesting the disease symptoms among controls at the time of recruitment does not guarantee that the individual will not develop the disease of interest in the future. Age-matched disease-free controls may be a better solution in similar situations. Different analytical techniques are also available that can be used to identify pleiotropic effects. Known pleiotropic effects can be searched from various online databases. Conclusion: Pleiotropic effects may result in bias in genetic association studies. Suggestions consist of selecting healthy yet age-matched controls and considering diseases with independent genetic architecture. Checking the related databases is recommended before designing a study.

Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers.

BACKGROUND: The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation. METHODS: We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values. RESULTS: A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response. CONCLUSIONS: The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.