A study of the association between single nucleotide polymorphisms of the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene and the risk of ankylosing spondylitis in Egyptians.

BACKGROUND: Ankylosing spondylitis (AS) is often regarded as the prototypical manifestation of spondylo-arthropathies that prevalently involves the axial skeleton with the potential attribution of ERAP2 polymorphisms to AS predisposition. The purpose of this study was to determine the genetic association between ERAP2 gene rs2910686, and rs2248374 single nucleotide polymorphisms (SNPs) and the risk of ankylosing spondylitis in the Egyptian population. METHODS AND RESULTS: A cross-sectional work involved 200 individuals: 100 AS individuals diagnosed based on modified New York criteria in 1984 with 100 healthy controls matched in age and gender. The study included a comprehensive evaluation of historical data, clinical examinations, and evaluation of the activity of the disease using the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). A comprehensive laboratory and radiological evaluation were conducted, accompanied by an assessment and genotyping of the ERAP2 gene variants rs2248374 and rs2910686. This genotyping was performed utilizing a real-time allelic discrimination methodology.Highly statistically substantial variations existed among the AS patients and the healthy control group regarding rs2910686 and rs2248374 alleles. There was a statistically significant difference between rs2910686 and rs2248374 regarding BASDAI, BASFI, mSASSS, ASQoL, V.A.S, E.S.R, and BASMI in the active AS group. CONCLUSIONS: ERAP2 gene SNPs have been identified as valuable diagnostic biomarkers for AS patients in the Egyptian population being a sensitive and non-invasive approach for AS diagnosis especially rs2910686. Highly statistically significant variations existed among the AS patients and the healthy control group regarding rs2910686 alleles and genotypes.Further research is recommended to explore the potential therapeutic implications of these SNPs.

Prenatal diagnosis of fetuses with absent/hypoplastic nasal bone in second-trimester using chromosomal microarray analysis.

BACKGROUND: Pathogenic copy number variants (pCNVs) are associated with fetal ultrasound anomalies, which can be efficiently identified through chromosomal microarray analysis (CMA). The primary objective of the present study was to enhance understanding of the genotype-phenotype correlation in fetuses exhibiting absent or hypoplastic nasal bones using CMA. METHODS: Enrolled in the present study were 94 cases of fetuses with absent/hypoplastic nasal bone, which were divided into an isolated absent/hypoplastic nasal bone group (n = 49) and a non-isolated group (n = 45). All pregnant women enrolled in the study underwent karyotype analysis and CMA to assess chromosomal abnormalities in the fetuses. RESULTS: Karyotype analysis and CMA detection were successfully performed in all cases. The results of karyotype and CMA indicate the presence of 11 cases of chromosome aneuploidy, with trisomy 21 being the most prevalent among them. A small supernumerary marker chromosome (sSMC) detected by karyotype analysis was further interpreted as a pCNV by CMA. Additionally, CMA detection elicited three cases of pCNVs, despite normal findings in their karyotype analysis results. Among them, one case of Roche translocation was identified to be a UPD in chromosome 15 with a low proportion of trisomy 15. Further, a significant difference in the detection rate of pCNVs was observed between non-isolated and isolated absent/hypoplastic nasal bone (24.44% vs. 8.16%, p < .05). CONCLUSION: The present study enhances the utility of CMA in diagnosing the etiology of absent or hypoplastic nasal bone in fetuses. Further, isolated cases of absent or hypoplastic nasal bone strongly suggest the presence of chromosomal abnormalities, necessitating genetic evaluation through CMA.

A novel method for multiple phenotype association studies based on genotype and phenotype network.

Joint analysis of multiple correlated phenotypes for genome-wide association studies (GWAS) can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits. Meanwhile, constructing a network based on associations between phenotypes and genotypes provides a new insight to analyze multiple phenotypes, which can explore whether phenotypes and genotypes might be related to each other at a higher level of cellular and organismal organization. In this paper, we first develop a bipartite signed network by linking phenotypes and genotypes into a Genotype and Phenotype Network (GPN). The GPN can be constructed by a mixture of quantitative and qualitative phenotypes and is applicable to binary phenotypes with extremely unbalanced case-control ratios in large-scale biobank datasets. We then apply a powerful community detection method to partition phenotypes into disjoint network modules based on GPN. Finally, we jointly test the association between multiple phenotypes in a network module and a single nucleotide polymorphism (SNP). Simulations and analyses of 72 complex traits in the UK Biobank show that multiple phenotype association tests based on network modules detected by GPN are much more powerful than those without considering network modules. The newly proposed GPN provides a new insight to investigate the genetic architecture among different types of phenotypes. Multiple phenotypes association studies based on GPN are improved by incorporating the genetic information into the phenotype clustering. Notably, it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy.

Distribution of pathogenic variants in the CFTR gene in a representative cohort of people with cystic fibrosis in the Kingdom of Bahrain.

BACKGROUND: Cystic fibrosis (CF) is a rare multi-systemic recessive disorder. The spectrum and the frequencies of CFTR mutations causing CF vary amongst different populations in Europe and the Middle East. In this study, we characterised the distribution of CF-causing mutations (i.e. pathogenic variants in the  CFTR gene) in a representative CF cohort from the Kingdom of Bahrain based on a three-decade-long analysis at a single tertiary centre. We aim to improve CF genetic diagnostics, introduce of CF neonatal screening and provide CFTR modulator therapy (CFTRm). METHODS: CFTR genotyping  and associated clinical information were drawn from a longitudinal cohort. We sequenced 56 people with CF (pwCF) that had one or both CFTR mutations unidentified and carried out comprehensive bioinformatic- and family-based segregation analyses of detected variants, including genotype-phenotype correlations and disease incidence estimates. The study methodology could serve as a basis for other non-European CF populations with a high degree of consanguinity. RESULTS: Altogether 18 CF-causing mutations  were identified, 15 of which were not previously detected in Bahrain, accounting for close to 100% of all population-specific alleles. The most common alleles comprise c.1911delG [2043delG; 22.8%], c.2988+1G > A [3120+1G>A; 16.3%], c.2989-1G>A [3121-1G>A; 14.1%], c.3909C>G [N1303K; 13.0%], and c.1521_1523delCTT [p.PheF508del; 7.6%]. Although the proportion of 1st cousin marriages has decreased to 50%, the frequency of homozygosity in our pwCF is 67.4%, thereby indicating that CF still occurs in large, often related, families. pwCF in Bahrain present with faltering growth, pancreatic insufficiency and classical sino-pulmonary manifestations. Interestingly, two pwCF also suffer from sickle cell disease. The estimated incidence of CF in Bahrain based on data from the last three decades is 1 in 9,880 live births. CONCLUSION: The most commonCF-causing  mutations in Bahraini pwCF were identified, enabling more precise diagnosis, introduction of two-tier neonatal screening and fostering administration of CFTRm.

Association of MTHFR (C677T, A1298C) and MTRR A66G polymorphisms with fatty acids profile and risk of neural tube defects.

OBJECTIVE: This study aims to determine if 5,10-methylenetetrahydrofolate reductase (MTHFR C677T and A1298C) and methionine synthase reductase (MTRR A66G) gene polymorphisms were associated with fatty acid (FA) levels in mothers of fetuses with neural tube defects (NTDs) and whether these associations were modified by environmental factors. METHODS: Plasma FA composition was assessed using capillary gas chromatography. Concentrations of studied FA were compared between 42 mothers of NTDs fetuses and 30 controls as a function of each polymorphism by the Kruskal-Wallis nonparametric test. RESULTS: In MTHFR gene C677T polymorphism, cases with (CT + TT) genotype had lower monounsaturated FAs (MUFA) and omega-3 polyunsaturated FA (n-3 PUFA) levels, but higher omega-6 polyunsaturated FAs (n-6 PUFA) and omega-6 polyunsaturated FAs: omega-3 polyunsaturated FAs (n-6:n-3) ratio levels. In MTRR gene A66G polymorphism, cases with (AG + GG) genotype had lower MUFA levels, but higher PUFA and n-6 PUFA levels. Controls with (AG + GG) genotype had lower n-6 PUFA levels. In MTHFR gene C677T polymorphism, cases with smoking spouses and (CT + TT) genotype had lower MUFA and n-3 PUFA levels, but higher PUFA, n-6 PUFA, and n-6:n-3 ratio levels. Cases with (CT + TT) genotype and who used sauna during pregnancy had lower n-3 PUFA levels. In MTRR gene A66G polymorphism, cases with (AG + GG) genotype and who used sauna during pregnancy had higher PUFA and n-6 PUFA levels. CONCLUSIONS: Further research is required to clarify the association of FA metabolism and (MTHFR, MTRR) polymorphisms with NTDs.

Exome sequencing in four families with neurodevelopmental disorders: genotype-phenotype correlation and identification of novel disease-causing variants in VPS13B and RELN.

Neurodevelopmental disorders (NDDs) are a clinically and genetically heterogeneous group of early-onset pediatric disorders that affect the structure and/or function of the central or peripheral nervous system. Achieving a precise molecular diagnosis for NDDs may be challenging due to the diverse genetic underpinnings and clinical variability. In the current study, we investigated the underlying genetic cause(s) of NDDs in four unrelated Pakistani families. Using exome sequencing (ES) as a diagnostic approach, we identified disease-causing variants in established NDD-associated genes in all families, including one hitherto unreported variant in RELN and three recurrent variants in VPS13B, DEGS1, and SPG11. Overall, our study highlights the potential of ES as a tool for clinical diagnosis.

The Association Between the 5-Hydroxytryptamine Receptor 2A Gene Variants rs6311 and rs6313 and Obstructive Sleep Apnea in the Iranian Kurdish Population.

Introduction: Sleep is one of the most significant parts of everyone's life. Most people sleep for about one-third of their lives. Sleep disorders negatively impact the quality of life. Obstructive sleep apnea (OSA) is a severe sleep disorder that significantly impacts the patient's life and their family members. This study aimed to investigate the relationship between rs6313 and rs6311 polymorphisms in the serotonin receptor type 2A gene and OSA in the Kurdish population. Materials and Methods: The study's population comprises 100 OSA sufferers and 100 healthy people. Polysomnography diagnostic tests were done on both the patient and control groups. The polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) was used to investigate the relationship between OSA and LEPR gene polymorphisms. Results: Statistical analysis showed a significant relationship between genotype frequencies of patient and control groups of rs6311 with OSA in dominant [odds ratio (OR) = 5.203, p < 0.001) and codominant models (OR = 9.7, p < 0.001). Also, there was a significant relationship between genotype frequencies of patient and control groups of rs6313 with OSA in dominant (OR = 10.565, p < 0.001) and codominant models (OR = 5.938, p < 0.001). Conclusions: Findings from the study demonstrated that the two polymorphisms rs6311 and rs6313 could be effective at causing OSA; however, there was no correlation between the severity of the disease and either of the two polymorphisms.

BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases.

Genome-wide Association Studies (GWAS) methods have identified individual single-nucleotide polymorphisms (SNPs) significantly associated with specific phenotypes. Nonetheless, many complex diseases are polygenic and are controlled by multiple genetic variants that are usually non-linearly dependent. These genetic variants are marginally less effective and remain undetected in GWAS analysis. Kernel-based tests (KBT), which evaluate the joint effect of a group of genetic variants, are therefore critical for complex disease analysis. However, choosing different kernel functions in KBT can significantly influence the type I error control and power, and selecting the optimal kernel remains a statistically challenging task. A few existing methods suffer from inflated type 1 errors, limited scalability, inferior power or issues of ambiguous conclusions. Here, we present a new Bayesian framework, BayesKAT (https://github.com/wangjr03/BayesKAT), which overcomes these kernel specification issues by selecting the optimal composite kernel adaptively from the data while testing genetic associations simultaneously. Furthermore, BayesKAT implements a scalable computational strategy to boost its applicability, especially for high-dimensional cases where other methods become less effective. Based on a series of performance comparisons using both simulated and real large-scale genetics data, BayesKAT outperforms the available methods in detecting complex group-level associations and controlling type I errors simultaneously. Applied on a variety of groups of functionally related genetic variants based on biological pathways, co-expression gene modules and protein complexes, BayesKAT deciphers the complex genetic basis and provides mechanistic insights into human diseases.

C9ORF72 hexanucleotide repeat expansion: From ALS and FTD to a broader pathogenic role?

The major gene underlying monogenic forms of amyotrophic lateral sclerosis (ALS) and fronto-temporal dementia (FTD) is C9ORF72. The causative mutation in C9ORF72 is an abnormal hexanucleotide (G4C2) repeat expansion (HRE) located in the first intron of the gene. The aim of this review is to propose a comprehensive update on recent developments on clinical, biological and therapeutics aspects related to C9ORF72 in order to highlight the current understanding of genotype-phenotype correlations, and also on biological machinery leading to neuronal death. We will particularly focus on the broad phenotypic presentation of C9ORF72-related diseases, that goes well beyond the classical phenotypes observed in ALS and FTD patients. Last, we will comment the possible therapeutical hopes for patients carrying a C9ORF72 HRE.

Variance-components tests for genetic association with multiple interval-censored outcomes.

Massive genetic compendiums such as the UK Biobank have become an invaluable resource for identifying genetic variants that are associated with complex diseases. Due to the difficulties of massive data collection, a common practice of these compendiums is to collect interval-censored data. One challenge in analyzing such data is the lack of methodology available for genetic association studies with interval-censored data. Genetic effects are difficult to detect because of their rare and weak nature, and often the time-to-event outcomes are transformed to binary phenotypes for access to more powerful signal detection approaches. However transforming the data to binary outcomes can result in loss of valuable information. To alleviate such challenges, this work develops methodology to associate genetic variant sets with multiple interval-censored outcomes. Testing sets of variants such as genes or pathways is a common approach in genetic association settings to lower the multiple testing burden, aggregate small effects, and improve interpretations of results. Instead of performing inference with only a single outcome, utilizing multiple outcomes can increase statistical power by aggregating information across multiple correlated phenotypes. Simulations show that the proposed strategy can offer significant power gains over a single outcome approach. We apply the proposed test to the investigation that motivated this study, a search for the genes that perturb risks of bone fractures and falls in the UK Biobank.

Cerebral visual impairment: genetic diagnoses and phenotypic associations.

BACKGROUND: Cerebral visual impairment (CVI) is the most common form of paediatric visual impairment in developed countries. CVI can arise from a host of genetic or acquired causes, but there has been limited research to date on CVI in the context of genetic disorders. METHODS: We carried out a retrospective analysis of genotypic and phenotypic data for participants with CVI within the DECIPHER database and 100 000 Genomes Project (100KGP). RESULTS: 158 individuals with CVI were identified across both cohorts. Within this group, pathogenic or likely pathogenic sequence variants in 173 genes were identified. 25 of these genes already have known associations with CVI, while the remaining 148 are candidate genes for this phenotype. Gene ontology analysis of the CVI gene sets from both DECIPHER and 100KGP suggests that CVI has a similar degree of genetic heterogeneity to other neurodevelopmental phenotypes, and a strong association with genetic variants converging on ion channels and receptor functions. Individuals with a monogenic disorder and CVI have a higher frequency of epilepsies and severe neurodisability than individuals with a monogenic disorder but not CVI. CONCLUSION: This study supports the availability of genetic testing for individuals with CVI alongside other neurodevelopmental difficulties. It also supports the availability of ophthalmological screening for individuals with genetic diagnoses linked to CVI. Further studies could elaborate on the links between specific genetic disorders, visual maturation and broader neurodevelopmental characteristics.

X-linked congenital adrenal hypoplasia: Report of long clinical follow-up and description of a new complex variant in the NR0B1 gene.

Adrenal hypoplasia congenita, attributed to NR0B1 pathogenic variants, accounts for more than 50% of the incidence of primary adrenal insufficiency in children. Although more than 250 different deleterious variations have been described, no genotype-phenotype correlation has been defined to date. We report a case of an adopted boy who reported the onset of an adrenal crisis at 2 weeks of age, requiring replacement therapy with mineralocorticoids and glucocorticoids for 4 months. For 3 years, he did well without treatment. At almost 4 years of age, the disorder was restarted. A long follow-up showed the evolution of hypogonadotropic hypogonadism. Molecular studies on NR0B1 revealed a novel and deleterious deletion-insertion-inversion-deletion complex rearrangement sorted in the 5'-3' direction, which is described as follows: (1) deletion of the intergenic region (between TASL and NR0B1 genes) and 5' region, (2) insertion of a sequence containing 37 bp at the junction of the intergenic region of the TASL gene and a part of exon 1 of the NR0B1 gene, (3) inversion of a part of exon 1, (4) deletion of the final portion of exon 1 and exon 2 and beginning of the 3'UTR region, (5) maintenance of part of the intergenic sequence (between genes MAGEB1 and NR0B1, telomeric sense), (6) large posterior deletion, in the same sense. The path to molecular diagnosis was challenging and involved several molecular biology techniques. Evaluating the breakpoints in our patient, we assumed that it was a nonrecurrent rearrangement that had not yet been described. It may involve a repair mechanism known as nonhomologous end-joining (NHEJ), which joins two ends of DNA in an imprecise manner, generating an "information scar," represented herein by the 37 bp insertion. In addition, the local Xp21 chromosome architecture with sequences capable of modifying the DNA structure could impact the formation of complex rearrangements.

Clinical and Genetic Spectrum in a Large Cohort of Hereditary Spastic Paraplegia.

BACKGROUND: Next-generation sequencing-based molecular assessment has benefited the diagnosis of hereditary spastic paraplegia (HSP) subtypes. However, the clinical and genetic spectrum of HSP due to large fragment deletions/duplications has yet to be fully defined. OBJECTIVE: We aim to better characterize the clinical phenotypes and genetic features of HSP and to provide new thoughts on diagnosis. METHODS: Whole-exome sequencing (WES) was performed in patients with clinically suspected HSP, followed by multiple ligation-dependent probe amplification (MLPA) sequentially carried out for those with negative findings in known causative genes. Genotype-phenotype correlation analyses were conducted under specific genotypes. RESULTS: We made a genetic diagnosis in 60% (162/270) of patients, of whom 48.9% (132/270) had 24 various subtypes due to point mutations (SPG4/SPG11/SPG35/SPG7/SPG10/SPG5/SPG3A/SPG2/SPG76/SPG30/SPG6/SPG9A/SPG12/SPG15/SPG17/SPG18/SPG26/SPG49/SPG55/SPG56/SPG57/SPG62/SPG78/SPG80). Thirty patients were found to have causative rearrangements by MLPA (11.1%), among which SPG4 was the most prevalent (73.3%), followed by SPG3A (16.7%), SPG6 (3.3%), SPG7 (3.3%), and SPG11 (3.3%). Clinical analysis showed that some symptoms were often related to specific subtypes, and rearrangement-related SPG3A patients seemingly had later onset. We observed a presumptive anticipation among SPG4 and SPG3A families due to rearrangement. CONCLUSIONS: Based on the largest known Asian HSP cohort, including the largest subgroup of rearrangement-related pedigrees, we gain a comprehensive understanding of the clinical and genetic spectrum of HSP. We propose a diagnostic flowchart to sequentially detect the causative genes in practice. Large fragment mutations account for a considerable proportion of HSP, and thus, MLPA screening acts as a beneficial supplement to routine WES. © 2024 International Parkinson and Movement Disorder Society.

Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders.

Autism spectrum disorder (ASD) comprises a large group of neurodevelopmental conditions featuring, over a wide range of severity and combinations, a core set of manifestations (restricted sociality, stereotyped behavior and language impairment) alongside various comorbidities. Common and rare variants in several hundreds of genes and regulatory regions have been implicated in the molecular pathogenesis of ASD along a range of causation evidence strength. Despite significant progress in elucidating the impact of few paradigmatic individual loci, such sheer complexity in the genetic architecture underlying ASD as a whole has hampered the identification of convergent actionable hubs hypothesized to relay between the vastness of risk alleles and the core phenotypes. In turn this has limited the development of strategies that can revert or ameliorate this condition, calling for a systems-level approach to probe the cross-talk of cooperating genes in terms of causal interaction networks in order to make convergences experimentally tractable and reveal their clinical actionability. As a first step in this direction, we have captured from the scientific literature information on the causal links between the genes whose variants have been associated with ASD and the whole human proteome. This information has been annotated in a computer readable format in the SIGNOR database and is made freely available in the resource website. To link this information to cell functions and phenotypes, we have developed graph algorithms that estimate the functional distance of any protein in the SIGNOR causal interactome to phenotypes and pathways. The main novelty of our approach resides in the possibility to explore the mechanistic links connecting the suggested gene-phenotype relations.

Unveiling facial kinship: The BioKinVis dataset for facial kinship verification and genetic association studies.

Facial image-based kinship verification represents a burgeoning frontier within the realms of computer vision and biomedicine. Recent genome-wide association studies have underscored the heritability of human facial morphology, revealing its predictability based on genetic information. These revelations form a robust foundation for advancing facial image-based kinship verification. Despite strides in computer vision, there remains a discernible gap between the biomedical and computer vision domains. Notably, the absence of family photo datasets established through biological paternity testing methods poses a significant challenge. This study addresses this gap by introducing the biological kinship visualization dataset, encompassing 5773 individuals from 2412 families with biologically confirmed kinship. Our analysis delves into the distribution and influencing factors of facial similarity among parent-child pairs, probing the potential association between forensic short tandem repeat polymorphisms and facial similarity. Additionally, we have developed a machine learning model for facial image-based kinship verification, achieving an accuracy of 0.80 in the dataset. To facilitate further exploration, we have established an online tool and database, accessible at http://120.55.161.230:88/.

Transcriptional linkage analysis with in vivo AAV-Perturb-seq.

The ever-growing compendium of genetic variants associated with human pathologies demands new methods to study genotype-phenotype relationships in complex tissues in a high-throughput manner1,2. Here we introduce adeno-associated virus (AAV)-mediated direct in vivo single-cell CRISPR screening, termed AAV-Perturb-seq, a tuneable and broadly applicable method for transcriptional linkage analysis as well as high-throughput and high-resolution phenotyping of genetic perturbations in vivo. We applied AAV-Perturb-seq using gene editing and transcriptional inhibition to systematically dissect the phenotypic landscape underlying 22q11.2 deletion syndrome3,4 genes in the adult mouse brain prefrontal cortex. We identified three 22q11.2-linked genes involved in known and previously undescribed pathways orchestrating neuronal functions in vivo that explain approximately 40% of the transcriptional changes observed in a 22q11.2-deletion mouse model. Our findings suggest that the 22q11.2-deletion syndrome transcriptional phenotype found in mature neurons may in part be due to the broad dysregulation of a class of genes associated with disease susceptibility that are important for dysfunctional RNA processing and synaptic function. Our study establishes a flexible and scalable direct in vivo method to facilitate causal understanding of biological and disease mechanisms with potential applications to identify genetic interventions and therapeutic targets for treating disease.

Network expansion of genetic associations defines a pleiotropy map of human cell biology.

Interacting proteins tend to have similar functions, influencing the same organismal traits. Interaction networks can be used to expand the list of candidate trait-associated genes from genome-wide association studies. Here, we performed network-based expansion of trait-associated genes for 1,002 human traits showing that this recovers known disease genes or drug targets. The similarity of network expansion scores identifies groups of traits likely to share an underlying genetic and biological process. We identified 73 pleiotropic gene modules linked to multiple traits, enriched in genes involved in processes such as protein ubiquitination and RNA processing. In contrast to gene deletion studies, pleiotropy as defined here captures specifically multicellular-related processes. We show examples of modules linked to human diseases enriched in genes with known pathogenic variants that can be used to map targets of approved drugs for repurposing. Finally, we illustrate the use of network expansion scores to study genes at inflammatory bowel disease genome-wide association study loci, and implicate inflammatory bowel disease-relevant genes with strong functional and genetic support.

Association of single nucleotide polymorphisms of interferon-γ with pulmonary tuberculosis in population of Himachal Pradesh, India.

Interferon-gamma (IFN-γ) plays an integral role in the host immunity against tuberculosis (TB). The gene encoding IFN-γ is polymorphic and several studies have reported the association of its genetic polymorphisms with TB in different populations of the world. The present study investigated the association of rs2069705 (C/T), rs1861494 (C/T), rs1861493 (A/G) and rs2069718 (C/T) single nucleotide polymorphisms (SNPs) of IFN-γ with pulmonary TB in a population of Himachal Pradesh, India. For present study, 210 pulmonary TB patients and 205 healthy controls (HCs) were recruited. The selected SNPs of IFN-γ were genotyped by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) and plasma IFN-γ levels were measured by ELISA. The 'T' allele of rs1861494 SNP was found to increase susceptibility to TB in the studied population (OR = 2.18, 95%CI = 1.57-3.03; p < 0.001). After stratifying the subjects on basis of sex, males with 'T' allele of rs2069718 SNP were found to be at higher risk to TB (OR = 1.55, 95%CI = 1.07-2.25; p = 0.02). We also found moderate linkage disequilibrium among the studied SNPs. The haplotypes C-T-A-T and T-T-G-T of rs2069705-rs1861494-rs1861493-rs2069718 were overrepresented in TB patients and found to increase susceptibility to TB (p = 0.012). The plasma IFN-γ levels in TB patients were around seven times higher in comparison to HCs (p < 0.0001). The HCs with genotype 'AA' of SNP rs1861493 were found with higher plasma IFN-γ levels than 'AG/GG' genotype (p = 0.023). In conclusion, the results suggest the association of rs1861494 (C/T) and rs2069718 (C/T) SNPs of IFN-γ with TB and genotype 'AA' of rs1861493 is associated with higher plasma IFN-γ levels in the population of Himachal Pradesh, India.

Placental genomics mediates genetic associations with complex health traits and disease.

As the master regulator in utero, the placenta is core to the Developmental Origins of Health and Disease (DOHaD) hypothesis but is historically understudied. To identify placental gene-trait associations (GTAs) across the life course, we perform distal mediator-enriched transcriptome-wide association studies (TWAS) for 40 traits, integrating placental multi-omics from the Extremely Low Gestational Age Newborn Study. At [Formula: see text], we detect 248 GTAs, mostly for neonatal and metabolic traits, across 176 genes, enriched for cell growth and immunological pathways. In aggregate, genetic effects mediated by placental expression significantly explain 4 early-life traits but no later-in-life traits. 89 GTAs show significant mediation through distal genetic variants, identifying hypotheses for distal regulation of GTAs. Investigation of one hypothesis in human placenta-derived choriocarcinoma cells reveal that knockdown of mediator gene EPS15 upregulates predicted targets SPATA13 and FAM214A, both associated with waist-hip ratio in TWAS, and multiple genes involved in metabolic pathways. These results suggest profound health impacts of placental genomic regulation in developmental programming across the life course.

Variation in caprine KRTAP1-3 and its association with cashmere fibre diameter.

Keratin-associated proteins (KAPs) are components of cashmere fibres. The gene encoding the KAP1-3 protein (KRTAP1-3) has been described in goats, but little is known about sequence variation in this gene and if it affects cashmere fibre traits. In this study, we used a polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) technique to screen for nucleotide sequence variation in caprine KRTAP1-3 in 327 Longdong cashmere goats, then analysed association between the genetic variation that was revealed and some cashmere fibre traits. Six PCR-SSCP patterns representing six different variant sequences of KRTAP1-3 (named A to F) were revealed. Among these variant sequences, seven single nucleotide polymorphisms (SNPs) were detected, with two of them being non-synonymous. Goats with genotype AC had higher mean fibre diameter (MFD) than those with genotype AB (P < 0.001), while goats with genotype AB had higher MFD than those with AA (P < 0.001). The presence of C (P < 0.001) and B (P = 0.006) in a genotype was associated with increased MFD, and together this suggests that variation in caprine KRTAP1-3 affects the key fibre trait of MFD.