A mathematical framework for genetic relatedness analysis involving X chromosome aneuploidies.

The unique features of the X chromosome can be crucial to complement autosomal profiling or to disentangle complex kinship problems, providing in some cases a similar or even greater power than autosomes in paternity/maternity investigations. While theoretical and informatics approaches for pairwise X-linked kinship analyses are well established for euploid individuals, these are still lacking for individuals with an X chromosome aneuploidy. To trigger the fulfilment of this gap, this research presents a mathematical framework that enables the quantification of DNA evidence in pairwise kinship analyses, involving two non-inbred individuals, one of whom with a non-mosaic X chromosome aneuploidy: Trisomy X (47, XXX), Klinefelter (47, XXY) or Turner (45, X0) syndrome. As previously developed for a regular number of chromosomes, this approach relies on the probability of related individuals sharing identical-by-descent (IBD) alleles at one specific locus and it can be applied to any set of independently transmitted markers, with no gametic association in the population. The kinship hypotheses mostly considered in forensic casework are specifically addressed in this work, but the reasoning and procedure can be applied to virtually any pairwise kinship problem under the referred assumptions. Algebraic formulae for joint genotypic probabilities cover all the possible genotypic configurations and pedigrees. Compared with the analyses assuming individuals with a regular number of chromosomes, complicating factors rely on the different possibilities for both the parental origin of the error (either maternal or paternal), and the type of error occurred (either meiotic or post-zygotic mitotic). These imply that a non-inbred female with Triple X or a male with Klinefelter syndrome may carry two IBD alleles at the same locus. Thus, and contrarily to what occurs for the standard case, IBD partitions depend not only on the kinship hypothesis under analysis but also on the genotypic configuration of the analyzed individuals. For some cases, parameters of interest can be inferred, while for others recommended values based on the available literature are provided. This work is the starting point to analyze X-chromosomal data under the scope of kinship problems, involving individuals with aneuploidies, as it will enhance the quantification of the DNA evidence not only in forensics but also in the medical genetics field. We hope it will trigger the development of approaches including other complicating factors, as a greater number of individuals, possibility of the occurrence of mutations and/or silent alleles, as well as the analysis of linked markers.

Microsatellites' mutation modeling through the analysis of the Y-chromosomal transmission: Results of a GHEP-ISFG collaborative study.

The Spanish and Portuguese Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) organized a collaborative study on mutations of Y-chromosomal short tandem repeats (Y-STRs). New data from 2225 father-son duos and data from 44 previously published reports, corresponding to 25,729 duos, were collected and analyzed. Marker-specific mutation rates were estimated for 33 Y-STRs. Although highly dependent on the analyzed marker, mutations compatible with the gain or loss of a single repeat were 23.2 times more likely than those involving a greater number of repeats. Longer alleles (relatively to the modal one) showed to be nearly twice more mutable than the shorter ones. Within the subset of longer alleles, the loss of repeats showed to be nearly twice more likely than the gain. Conversely, shorter alleles showed a symmetrical trend, with repeat gains being twofold more frequent than reductions. A positive correlation between the paternal age and the mutation rate was observed, strengthening previous findings. The results of a machine learning approach, via logistic regression analyses, allowed the establishment of algebraic formulas for estimating the probability of mutation depending on paternal age and allele length for DYS389I, DYS393 and DYS627. Algebraic formulas could also be established considering only the allele length as predictor for DYS19, DYS389I, DYS389II-I, DYS390, DYS391, DYS393, DYS437, DYS439, DYS449, DYS456, DYS458, DYS460, DYS481, DYS518, DYS533, DYS576, DYS626 and DYS627 loci. For the remaining Y-STRs, a lack of statistical significance was observed, probably as a consequence of the small effective size of the subsets available, a common difficulty in the modeling of rare events as is the case of mutations. The amount of data used in the different analyses varied widely, depending on how the data were reported in the publications analyzed. This shows a regrettable waste of produced data, due to inadequate communication of the results, supporting an urgent need of publication guidelines for mutation studies.

Integrating functional scoring and regulatory data to predict the effect of non-coding SNPs in a complex neurological disease.

Most SNPs associated with complex diseases seem to lie in non-coding regions of the genome; however, their contribution to gene expression and disease phenotype remains poorly understood. Here, we established a workflow to provide assistance in prioritising the functional relevance of non-coding SNPs of candidate genes as susceptibility loci in polygenic neurological disorders. To illustrate the applicability of our workflow, we considered the multifactorial disorder migraine as a model to follow our step-by-step approach. We annotated the overlap of selected SNPs with regulatory elements and assessed their potential impact on gene expression based on publicly available prediction algorithms and functional genomics information. Some migraine risk loci have been hypothesised to reside in non-coding regions and to be implicated in the neurotransmission pathway. In this study, we used a set of 22 non-coding SNPs from neurotransmission and synaptic machinery-related genes previously suggested to be involved in migraine susceptibility based on our candidate gene association studies. After prioritising these SNPs, we focused on non-reported ones that demonstrated high regulatory potential: (1) VAMP2_rs1150 (3' UTR) was predicted as a target of hsa-mir-5010-3p miRNA, possibly disrupting its own gene expression; (2) STX1A_rs6951030 (proximal enhancer) may affect the binding affinity of zinc-finger transcription factors (namely ZNF423) and disturb TBL2 gene expression; and (3) SNAP25_rs2327264 (distal enhancer) expected to be in a binding site of ONECUT2 transcription factor. This study demonstrated the applicability of our practical workflow to facilitate the prioritisation of potentially relevant non-coding SNPs and predict their functional impact in multifactorial neurological diseases.

Non-coding variants in VAMP2 and SNAP25 affect gene expression: potential implications in migraine susceptibility.

Migraine is a common and complex neurological disease potentially caused by a polygenic interaction of multiple gene variants. Many genes associated with migraine are involved in pathways controlling the synaptic function and neurotransmitters release. However, the molecular mechanisms underpinning migraine need to be further explored.Recent studies raised the possibility that migraine may arise from the effect of regulatory non-coding variants. In this study, we explored the effect of candidate non-coding variants potentially associated with migraine and predicted to lie within regulatory elements: VAMP2_rs1150, SNAP25_rs2327264, and STX1A_rs6951030. The involvement of these genes, which are constituents of the SNARE complex involved in membrane fusion and neurotransmitter release, underscores their significance in migraine pathogenesis. Our reporter gene assays confirmed the impact of at least two of these non-coding variants. VAMP2 and SNAP25 risk alleles were associated with a decrease and increase in gene expression, respectively, while STX1A risk allele showed a tendency to reduce luciferase activity in neuronal-like cells. Therefore, the VAMP2_rs1150 and SNAP25_rs2327264 non-coding variants affect gene expression, which may have implications in migraine susceptibility. Based on previous in silico analysis, it is plausible that these variants influence the binding of regulators, such as transcription factors and micro-RNAs. Still, further studies exploring these mechanisms would be important to shed light on the association between SNAREs dysregulation and migraine susceptibility.

The sequence of the repetitive motif influences the frequency of multistep mutations in Short Tandem Repeats.

Microsatellites, or Short Tandem Repeats (STRs), are subject to frequent length mutations that involve the loss or gain of an integer number of repeats. This work aimed to investigate the correlation between STRs' specific repetitive motif composition and mutational dynamics, specifically the occurrence of single- or multistep mutations. Allelic transmission data, comprising 323,818 allele transfers and 1,297 mutations, were gathered for 35 Y-chromosomal STRs with simple structure. Six structure groups were established: ATT, CTT, TCTA/GATA, GAAA/CTTT, CTTTT, and AGAGAT, according to the repetitive motif present in the DNA leading strand of the markers. Results show that the occurrence of multistep mutations varies significantly among groups of markers defined by the repetitive motif. The group of markers with the highest frequency of multistep mutations was the one with repetitive motif CTTTT (25% of the detected mutations) and the lowest frequency corresponding to the group with repetitive motifs TCTA/GATA (0.93%). Statistically significant differences (α = 0.05) were found between groups with repetitive motifs with different lengths, as is the case of TCTA/GATA and ATT (p = 0.0168), CTT (p < 0.0001) and CTTTT (p < 0.0001), as well as between GAAA/CTTT and CTTTT (p = 0.0102). The same occurred between the two tetrameric groups GAAA/CTTT and TCTA/GATA (p < 0.0001) - the first showing 5.7 times more multistep mutations than the second. When considering the number of repeats of the mutated paternal alleles, statistically significant differences were found for alleles with 10 or 12 repeats, between GATA and ATT structure groups. These results, which demonstrate the heterogeneity of mutational dynamics across repeat motifs, have implications in the fields of population genetics, epidemiology, or phylogeography, and whenever STR mutation models are used in evolutionary studies in general.

Genotype-first approach to identify associations between CDH1 germline variants and cancer phenotypes: a multicentre study by the European Reference Network on Genetic Tumour Risk Syndromes.

BACKGROUND: Truncating pathogenic or likely pathogenic variants of CDH1 cause hereditary diffuse gastric cancer (HDGC), a tumour risk syndrome that predisposes carrier individuals to diffuse gastric and lobular breast cancer. Rare CDH1 missense variants are often classified as variants of unknown significance. We conducted a genotype-phenotype analysis in families carrying rare CDH1 variants, comparing cancer spectrum in carriers of pathogenic or likely pathogenic variants (PV/LPV; analysed jointly) or missense variants of unknown significance, assessing the frequency of families with lobular breast cancer among PV/LPV carrier families, and testing the performance of lobular breast cancer-expanded criteria for CDH1 testing. METHODS: This genotype-first study used retrospective diagnostic and clinical data from 854 carriers of 398 rare CDH1 variants and 1021 relatives, irrespective of HDGC clinical criteria, from 29 institutions in ten member-countries of the European Reference Network on Tumour Risk Syndromes (ERN GENTURIS). Data were collected from Oct 1, 2018, to Sept 20, 2022. Variants were classified by molecular type and clinical actionability with the American College of Medical Genetics and Association for Molecular Pathology CDH1 guidelines (version 2). Families were categorised by whether they fulfilled the 2015 and 2020 HDGC clinical criteria. Genotype-phenotype associations were analysed by Student's t test, Kruskal-Wallis, χ2, and multivariable logistic regression models. Performance of HDGC clinical criteria sets were assessed with an equivalence test and Youden index, and the areas under the receiver operating characteristic curves were compared by Z test. FINDINGS: From 1971 phenotypes (contributed by 854 probands and 1021 relatives aged 1-93 years), 460 had gastric and breast cancer histology available. CDH1 truncating PV/LPVs occurred in 176 (21%) of 854 families and missense variants of unknown significance in 169 (20%) families. Multivariable logistic regression comparing phenotypes occurring in families carrying PV/LPVs or missense variants of unknown significance showed that lobular breast cancer had the greatest positive association with the presence of PV/LPVs (odds ratio 12·39 [95% CI 2·66-57·74], p=0·0014), followed by diffuse gastric cancer (8·00 [2·18-29·39], p=0·0017) and gastric cancer (7·81 [2·03-29·96], p=0·0027). 136 (77%) of 176 families carrying PV/LPVs fulfilled the 2015 HDGC criteria. Of the remaining 40 (23%) families, who did not fulfil the 2015 criteria, 11 fulfilled the 2020 HDGC criteria, and 18 had lobular breast cancer only or lobular breast cancer and gastric cancer, but did not meet the 2020 criteria. No specific CDH1 variant was found to predispose individuals specifically to lobular breast cancer, although 12 (7%) of 176 PV/LPV carrier families had lobular breast cancer only. Addition of three new lobular breast cancer-centred criteria improved testing sensitivity while retaining high specificity. The probability of finding CDH1 PV/LPVs in patients fulfilling the lobular breast cancer-expanded criteria, compared with the 2020 criteria, increased significantly (AUC 0·92 vs 0·88; Z score 3·54; p=0·0004). INTERPRETATION: CDH1 PV/LPVs were positively associated with HDGC-related phenotypes (lobular breast cancer, diffuse gastric cancer, and gastric cancer), and no evidence for a positive association with these phenotypes was found for CDH1 missense variants of unknown significance. CDH1 PV/LPVs occurred often in families with lobular breast cancer who did not fulfil the 2020 HDGC criteria, supporting the expansion of lobular breast cancer-centred criteria. FUNDING: European Reference Network on Genetic Tumour Risk Syndromes, European Regional Development Fund, Fundação para a Ciência e a Tecnologia (Portugal), Cancer Research UK, and European Union's Horizon 2020 research and innovation programme.

Estimations of Mutation Rates Depend on Population Allele Frequency Distribution: The Case of Autosomal Microsatellites.

Microsatellites (or short-tandem repeats (STRs)) are widely used in anthropology and evolutionary studies. Their extensive polymorphism and rapid evolution make them the ideal genetic marker for dating events, such as the age of a gene or a population. This usage requires the estimation of mutation rates, which are usually estimated by counting the observed Mendelian incompatibilities in one-generation familial configurations (typically parent(s)-child duos or trios). Underestimations are inevitable when using this approach, due to the occurrence of mutational events that do not lead to incompatibilities with the parental genotypes ('hidden' or 'covert' mutations). It is known that the likelihood that one mutation event leads to a Mendelian incompatibility depends on the mode of genetic transmission considered, the type of familial configuration (duos or trios) considered, and the genotype(s) of the progenitor(s). In this work, we show how the magnitude of the underestimation of autosomal microsatellite mutation rates varies with the populations' allele frequency distribution spectrum. The Mendelian incompatibilities approach (MIA) was applied to simulated parent(s)/offspring duos and trios in different populational scenarios. The results showed that the magnitude and type of biases depend on the population allele frequency distribution, whatever the type of familial data considered, and are greater when duos, instead of trios, are used to obtain the estimates. The implications for molecular anthropology are discussed and a simple framework is presented to correct the naïf estimates, along with an informatics tool for the correction of incompatibility rates obtained through the MIA.

A High Methylation Level of a Novel -284 bp CpG Island in the RAMP1 Gene Promoter Is Potentially Associated with Migraine in Women.

Migraine is a complex neurovascular disorder affecting one billion people worldwide, mainly females. It is characterized by attacks of moderate to severe headache pain, with associated symptoms. Receptor activity modifying protein (RAMP1) is part of the Calcitonin Gene-Related Peptide (CGRP) receptor, a pharmacological target for migraine. Epigenetic processes, such as DNA methylation, play a role in clinical presentation of various diseases. DNA methylation occurs mostly in the gene promoter and can control gene expression. We investigated the methylation state of the RAMP1 promoter in 104 female blood DNA samples: 54 migraineurs and 50 controls. We treated DNA with sodium bisulfite and performed PCR, Sanger Sequencing, and Epigenetic Sequencing Methylation (ESME) software analysis. We identified 51 CpG dinucleotides, and 5 showed methylation variability. Migraineurs had a higher number of individuals with all five CpG methylated when compared to controls (26% vs. 16%), although non-significant (p = 0.216). We also found that CpG -284 bp, related to the transcription start site (TSS), showed higher methylation levels in cases (p = 0.011). This CpG may potentially play a role in migraine, affecting RAMP1 transcription or receptor malfunctioning and/or altered CGRP binding. We hope to confirm this finding in a larger cohort and establish an epigenetic biomarker to predict female migraine risk.

Quantification of forensic genetic evidence: Comparison of results obtained by qualitative and quantitative software for real casework samples.

To overcome the multifactorial complexity associated with the analysis and interpretation of the capillary electrophoresis results of forensic mixture samples, probabilistic genotyping methods have been developed and implemented as software, based on either qualitative or quantitative models. The former considers the electropherograms' qualitative information (detected alleles), whilst the latter also takes into account the associated quantitative information (height of allele peaks). Both models then quantify the genetic evidence through the computation of a likelihood ratio (LR), comparing the probabilities of the observations given two alternative and mutually exclusive hypotheses. In this study, the results obtained through the qualitative software LRmix Studio (v.2.1.3), and the quantitative ones: STRmix™ (v.2.7) and EuroForMix (v.3.4.0), were compared considering real casework samples. A set of 156 irreversibly anonymized sample pairs (GeneMapper files), obtained under the scope of former cases of the Portuguese Scientific Police Laboratory, Judiciary Police (LPC-PJ), were independently analyzed using each software. Sample pairs were composed by (i) a mixture profile with either two or three estimated contributors, and (ii) a single contributor profile associated. In most cases, information on 21 short tandem repeat (STR) autosomal markers were considered, and the majority of the single-source samples could not be a priori excluded as belonging to a contributor to the paired mixture sample. This inter-software analysis shows the differences between the probative values obtained through different qualitative and quantitative tools, for the same input samples. LR values computed in this work by quantitative tools showed to be generally higher than those obtained by the qualitative. Although the differences between the LR values computed by both quantitative software showed to be much smaller, STRmix™ generated LRs are generally higher than those from EuroForMix. As expected, mixtures with three estimated contributors showed generally lower LR values than those obtained for mixtures with two estimated contributors. Different software products are based on different approaches and mathematical or statistical models, which necessarily result in the computation of different LR values. The understanding by the forensic experts of the models and their differences among available software is therefore crucial. The better the expert understands the methodology, the better he/she will be able to support and/or explain the results in court or any other area of scrutiny.

Influence of PICALM and CLU risk variants on beta EEG activity in Alzheimer's disease patients.

PICALM and CLU genes have been linked to alterations in brain biochemical processes that may have an impact on Alzheimer's disease (AD) development and neurophysiological dynamics. The aim of this study is to analyze the relationship between the electroencephalographic (EEG) activity and the PICALM and CLU alleles described as conferring risk or protective effects on AD patients and healthy controls. For this purpose, EEG activity was acquired from: 18 AD patients and 12 controls carrying risk alleles of both PICALM and CLU genes, and 35 AD patients and 12 controls carrying both protective alleles. Relative power (RP) in the conventional EEG frequency bands (delta, theta, alpha, beta, and gamma) was computed to quantify the brain activity at source level. In addition, spatial entropy (SE) was calculated in each band to characterize the regional distribution of the RP values throughout the brain. Statistically significant differences in global RP and SE at beta band (p-values < 0.05, Mann-Whitney U-test) were found between genotypes in the AD group. Furthermore, RP showed statistically significant differences in 58 cortical regions out of the 68 analyzed in AD. No statistically significant differences were found in the control group at any frequency band. Our results suggest that PICALM and CLU AD-inducing genotypes are involved in physiological processes related to disruption in beta power, which may be associated with physiological disturbances such as alterations in beta-amyloid and neurotransmitter metabolism.

Risk Variants in Three Alzheimer's Disease Genes Show Association with EEG Endophenotypes.

BACKGROUND: Dementia due to Alzheimer's disease (AD) is a complex neurodegenerative disorder, which much of heritability remains unexplained. At the clinical level, one of the most common physiological alterations is the slowing of oscillatory brain activity, measurable by electroencephalography (EEG). Relative power (RP) at the conventional frequency bands (i.e., delta, theta, alpha, beta-1, and beta-2) can be considered as AD endophenotypes. OBJECTIVE: The aim of this work is to analyze the association between sixteen genes previously related with AD: APOE, PICALM, CLU, BCHE, CETP, CR1, SLC6A3, GRIN2 ß, SORL1, TOMM40, GSK3 ß, UNC5C, OPRD1, NAV2, HOMER2, and IL1RAP, and the slowing of the brain activity, assessed by means of RP at the aforementioned frequency bands. METHODS: An Iberian cohort of 45 elderly controls, 45 individuals with mild cognitive impairment, and 109 AD patients in the three stages of the disease was considered. Genomic information and brain activity of each subject were analyzed. RESULTS: The slowing of brain activity was observed in carriers of risk alleles in IL1RAP (rs10212109, rs9823517, rs4687150), UNC5C (rs17024131), and NAV2 (rs1425227, rs862785) genes, regardless of the disease status and situation towards the strongest risk factors: age, sex, and APOE ɛ4 presence. CONCLUSION: Endophenotypes reduce the complexity of the general phenotype and genetic variants with a major effect on those specific traits may be then identified. The found associations in this work are novel and may contribute to the comprehension of AD pathogenesis, each with a different biological role, and influencing multiple factors involved in brain physiology.

4SpecID: Reference DNA Libraries Auditing and Annotation System for Forensic Applications.

Forensic genetics is a fast-growing field that frequently requires DNA-based taxonomy, namely, when evidence are parts of specimens, often highly processed in food, potions, or ointments. Reference DNA-sequences libraries, such as BOLD or GenBank, are imperative tools for taxonomic assignment, particularly when morphology is inadequate for classification. The auditing and curation of these datasets require reliable mechanisms, preferably with automated data preprocessing. Software tools were developed to grade these datasets considering as primary criterion the number of records, which is not compliant with forensic standards, where the priority is validation from independent sources. Moreover, 4SpecID is an efficient software tool developed to audit and annotate reference libraries, specifically designed for forensic applications. Its intuitive user-friendly interface virtually accesses any database and includes specific data mining functions tuned for the widespread BOLD repositories. The built tool was evaluated in laptop MacBook and a dual-Xeon server with a large BOLD dataset (Culicidae, 36,115 records), and the best execution time to grade the dataset on the laptop was 0.28 s. Datasets of Bovidae and Felidae families were used to evaluate the quality of the tool and the relevance of independent sources validation.

APOE Variants in an Iberian Alzheimer Cohort Detected through an Optimized Sanger Sequencing Protocol.

The primary genetic risk factor for late onset Alzheimer's disease (LOAD) is the APOE4 allele of Apolipoprotein E (APOE) gene. The three most common variants of APOE are determined by single nucleotide polymorphisms (SNPs) rs429358 and rs7412. Our aim was to estimate allele and genotype frequencies of APOE variants in an Iberian cohort, thus helping to understand differences in APOE-related LOAD risk observed across populations. We analyzed saliva or buccal swab samples from 229 LOAD patients and 89 healthy elderly controls (≥68 years old) from Northern Portugal and Castile and León region, Spain. The genotyping was performed by Sanger sequencing, optimized to overcome GC content drawbacks. Results obtained in our Iberian LOAD and control cohorts are in line with previous large meta-analyses on APOE frequencies in Caucasian populations; however, we found differences in allele frequencies between our Portuguese and Spanish subgroups of AD patients. Moreover, when comparing studies from Iberian and other Caucasian cohorts, differences in APOE2 and APOE4 frequencies and subsequent different APOE-related LOAD risks must be clarified. These results show the importance of studying genetic variation at the APOE gene in different populations (including analyses at a regional level) to increase our knowledge about its clinical significance.

Genome-Wide Scan for Five Brain Oscillatory Phenotypes Identifies a New QTL Associated with Theta EEG Band.

Brain waves, measured by electroencephalography (EEG), are a powerful tool in the investigation of neurophysiological traits and a noninvasive and cost-effective alternative in the diagnostic of some neurological diseases. In order to identify novel Quantitative Trait Loci (QTLs) for brain wave relative power (RP), we collected resting state EEG data in five frequency bands (δ, θ, α, ß1, and ß2) and genome-wide data in a cohort of 105 patients with late onset Alzheimer's disease (LOAD), 41 individuals with mild cognitive impairment and 45 controls from Iberia, correcting for disease status. One novel association was found with an interesting candidate for a role in brain wave biology, CLEC16A (C-type lectin domain family 16), with a variant at this locus passing the adjusted genome-wide significance threshold after Bonferroni correction. This finding reinforces the importance of immune regulation in brain function. Additionally, at a significance cutoff value of 5 × 10-6, 18 independent association signals were detected. These signals comprise brain expression Quantitative Loci (eQTLs) in caudate basal ganglia, spinal cord, anterior cingulate cortex and hypothalamus, as well as chromatin interactions in adult and fetal cortex, neural progenitor cells and hippocampus. Moreover, in the set of genes showing signals of association with brain wave RP in our dataset, there is an overrepresentation of loci previously associated with neurological traits and pathologies, evidencing the pleiotropy of the genetic variation modulating brain function.

Twenty Years Later: A Comprehensive Review of the X Chromosome Use in Forensic Genetics.

The unique structure of the X chromosome shaped by evolution has led to the present gender-specific genetic differences, which are not shared by its counterpart, the Y chromosome, and neither by the autosomes. In males, recombination between the X and Y chromosomes is limited to the pseudoautosomal regions, PAR1 and PAR2; therefore, in males, the X chromosome is (almost) entirely transmitted to female offspring. On the other hand, the X chromosome is present in females with two copies that recombine along the whole chromosome during female meiosis and that is transmitted to both female and male descendants. These transmission characteristics, besides the obvious clinical impact (sex chromosome aneuploidies are extremely frequent), make the X chromosome an irreplaceable genetic tool for population genetic-based studies as well as for kinship and forensic investigations. In the early 2000s, the number of publications using X-chromosomal polymorphisms in forensic and population genetic applications increased steadily. However, nearly 20 years later, we observe a conspicuous decrease in the rate of these publications. In light of this observation, the main aim of this article is to provide a comprehensive review of the advances and applications of X-chromosomal markers in population and forensic genetics over the last two decades. The foremost relevant topics are addressed as: (i) developments concerning the number and types of markers available, with special emphasis on short tandem repeat (STR) polymorphisms (STR nomenclatures and practical concerns); (ii) overview of worldwide population (frequency) data; (iii) the use of X-chromosomal markers in (complex) kinship testing and the forensic statistical evaluation of evidence; (iv) segregation and mutation studies; and (v) current weaknesses and future prospects.

Relationship between the Presence of the ApoE ε4 Allele and EEG Complexity along the Alzheimer's Disease Continuum.

Alzheimer's disease (AD) is the most prevalent cause of dementia, being considered a major health problem, especially in developed countries. Late-onset AD is the most common form of the disease, with symptoms appearing after 65 years old. Genetic determinants of AD risk are vastly unknown, though, ε 4 allele of the ApoE gene has been reported as the strongest genetic risk factor for AD. The objective of this study was to analyze the relationship between brain complexity and the presence of ApoE ε 4 alleles along the AD continuum. For this purpose, resting-state electroencephalography (EEG) activity was analyzed by computing Lempel-Ziv complexity (LZC) from 46 healthy control subjects, 49 mild cognitive impairment subjects, 45 mild AD patients, 44 moderate AD patients and 33 severe AD patients, subdivided by ApoE status. Subjects with one or more ApoE ε 4 alleles were included in the carriers subgroups, whereas the ApoE ε 4 non-carriers subgroups were formed by subjects without any ε 4 allele. Our results showed that AD continuum is characterized by a progressive complexity loss. No differences were observed between AD ApoE ε 4 carriers and non-carriers. However, brain activity from healthy subjects with ApoE ε 4 allele (carriers subgroup) is more complex than from non-carriers, mainly in left temporal, frontal and posterior regions (p-values < 0.05, FDR-corrected Mann-Whitney U-test). These results suggest that the presence of ApoE ε 4 allele could modify the EEG complexity patterns in different brain regions, as the temporal lobes. These alterations might be related to anatomical changes associated to neurodegeneration, increasing the risk of suffering dementia due to AD before its clinical onset. This interesting finding might help to advance in the development of new tools for early AD diagnosis.

Paternal and maternal mutations in X-STRs: A GHEP-ISFG collaborative study.

The GHEP-ISFG organized a collaborative study to estimate mutation rates for the markers included in the Investigator Argus X-12 QS kit Qiagen. A total of 16 laboratories gathered data from 1,612 father/mother/daughter trios, which were used to estimate both maternal and paternal mutation rates, when pooled together with other already published data. Data on fathers and mothers' age at the time of birth of the daughter were also available for ∼93 % of the cases. Population analyses were computed considering the genetic information of a subset of 1,327 unrelated daughters, corresponding to 2,654 haplotypes from residents in several regions of five countries: Argentina, Brazil, Ecuador, Portugal and Spain. Genetic differentiation analyses between the population samples from the same country did not reveal signs of significant stratification, although results from Hardy-Weinberg and linkage disequilibrium tests indicated the need of larger studies for Ecuador and Brazilian populations. The high genetic diversity of the markers resulted in a large number of haplotype combinations, showing the need of huge databases for reliable estimates of their frequencies. It should also be noted the high number of new alleles found, many of them not included in the allelic ladders provided with the kit, as very diverse populations were analyzed. The overall estimates for locus specific average mutation rates varied between 7.5E-04 (for DXS7423) and 1.1E-02 (for DXS10135), the latter being a troublesome figure for kinship analyses. Most of the found mutations (∼92 %) are compatible with the gain or loss of a single repeat. Paternal mutation rates showed to be 5.2 times higher than maternal ones. We also found that older fathers were more prone to transmit mutated alleles, having this trend not been observed in the case of the mothers.

Computational modeling of the effects of EEG volume conduction on functional connectivity metrics. Application to Alzheimer's disease continuum.

OBJECTIVE: The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume conduction in different measures of functional connectivity and to characterize the EEG coupling alterations at the different stages of dementia due to Alzheimer's disease (AD). APPROACH: Magnitude squared coherence (MSCOH), imaginary part of coherence (iCOH), lagged coherence (lagCOH), amplitude envelope correlation (AEC), synchronization likelihood (SL), phase lag index (PLI), phase locking value (PLV), and corrected imaginary PLV (ciPLV) were applied to: (i) synthetic signals generated with a Kuramoto-based model of several coupled oscillators; and (ii) a resting-state EEG database of real recordings from 51 cognitively healthy controls, 51 mild cognitive impairment (MCI) subjects, 51 mild AD (AD mil ) patients, 50 moderate AD (AD mod ) patients, and 50 severe AD (AD sev ) patients. MAIN RESULTS: Our results using synthetic signals showed that PLI was the least affected parameter by spurious influences in a simulated volume conduction environment. Results using real EEG recordings showed that spontaneous activity of MCI patients is characterized by a significant coupling increase in the [Formula: see text] band. As dementia progresses, this increase in the [Formula: see text] band became more pronounced, and a significant widespread decrease in [Formula: see text] band appeared at the last stage of dementia. SIGNIFICANCE: Our results revealed that the estimation of functional EEG connectivity using PLI could reduce the bias introduced by the spurious influence of volume conduction, and it could increase the insight into the underlying brain dynamics at different stages of the AD continuum.

EEG Characterization of the Alzheimer's Disease Continuum by Means of Multiscale Entropies.

Alzheimer's disease (AD) is a neurodegenerative disorder with high prevalence, known for its highly disabling symptoms. The aim of this study was to characterize the alterations in the irregularity and the complexity of the brain activity along the AD continuum. Both irregularity and complexity can be studied applying entropy-based measures throughout multiple temporal scales. In this regard, multiscale sample entropy (MSE) and refined multiscale spectral entropy (rMSSE) were calculated from electroencephalographic (EEG) data. Five minutes of resting-state EEG activity were recorded from 51 healthy controls, 51 mild cognitive impaired (MCI) subjects, 51 mild AD patients (ADMIL), 50 moderate AD patients (ADMOD), and 50 severe AD patients (ADSEV). Our results show statistically significant differences (p-values < 0.05, FDR-corrected Kruskal-Wallis test) between the five groups at each temporal scale. Additionally, average slope values and areas under MSE and rMSSE curves revealed significant changes in complexity mainly for controls vs. MCI, MCI vs. ADMIL and ADMOD vs. ADSEV comparisons (p-values < 0.05, FDR-corrected Mann-Whitney U-test). These findings indicate that MSE and rMSSE reflect the neuronal disturbances associated with the development of dementia, and may contribute to the development of new tools to track the AD progression.

Assessment of EEG Connectivity Patterns in Mild Cognitive Impairment Using Phase Slope Index.

Mild cognitive impairment (MCI) is a pathology characterized by an abnormal cognitive state. MCI patients are considered to be at high risk for developing dementia. The aim of this study is to characterize the changes that MCI causes in the patterns of brain information flow. For this purpose, spontaneous EEG activity from 41 MCI patients and 37 healthy controls was analyzed by means of an effective connectivity measure: the phase slope index (PSl). Our results showed statistically significant decreases in PSI values mainly at delta and alpha frequency bands for MCI patients, compared to the control group. These abnormal patterns may be due to the structural changes in the brain suffered by patients: decreased hippocampal volume, atrophy of the medial temporal lobe, or loss of gray matter volume. This study suggests the usefulness of PSI to provide further insights into the underlying brain dynamics associated with MCI.