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Andrew Hattersley

Publications and source records attributed to Andrew Hattersley.

8 recordsLinked to original sources
PubMed2006

Rapid and sensitive real-time polymerase chain reaction method for detection and quantification of 3243A>G mitochondrial point mutation.

Maternally inherited diabetes and deafness and mitochondrial encephalomyopathy, lactic acidosis with stroke-like episodes result from the 3243A>G mitochondrial point mutation. Current methods to detect the presence of the mutation have limited sensitivity and may lead to potential misclassification of patients with low levels of heteroplasmy. Here, we describe development and validation of a rapid real-time polymerase chain reaction (PCR) method for detection and quantification of levels of heteroplasmy in a single assay. Standard curve analysis indicated that the sensitivity of detection was less than 0.1%. Time from sample loading to data analysis was 110 minutes. We tested 293 samples including 23 known positives, 40 known negatives, and 230 samples from patients clinically classified as having type 2 diabetes. All positive samples were correctly detected, and of those samples previously quantified, heteroplasmy levels determined using the real-time assay correlated well (r(2) = 0.88 and 0.93) with results from fluorescently labeled PCR-restriction fragment length polymorphism and pyrosequencing methods. Screening of 230 patients classified as having type 2 diabetes revealed one patient with 0.6% heteroplasmy who had previously tested negative by PCR-restriction fragment length polymorphism. Real-time PCR provides rapid simultaneous detection and quantification of the 3243A>G mutation to a detection limit of less than 0.1%, without post-PCR manipulation.

Adenosine↗
PubMed2003

A meta-analysis of four European genome screens (GIFT Consortium) shows evidence for a novel region on chromosome 17p11.2-q22 linked to type 2 diabetes.

Positional cloning is expected to identify novel susceptibility genes underlying complex traits, but replication of genome-wide linkage scan findings has proven erratic. To improve our ability to detect and prioritize chromosomal regions containing type 2 diabetes susceptibility genes, the GIFT consortium has implemented a meta-analysis of four scans conducted in European samples. These included the Botnia I and Botnia II scans, with respectively 58 and 353 pedigrees from Finland and Sweden, the Warren 2 scan performed in 573 multiplex sibships from the UK, and a scan of 143 families from France. The meta-analysis was implemented using the genome-search analysis method (GSMA), an exploratory data analysis technique which is robust across study designs. The analysis provided evidence for linkage of type 2 diabetes to six regions, with the strongest evidence on chromosome 17p11.2-q22 (P=0.0016), followed by 2p22.1-p13.2 (P=0.027), 1p13.1-q22 (P=0.028), 12q21.1-q24.12 (P=0.029), 6q21-q24.1 (P=0.033) and 16p12.3-q11.2 (P=0.033). Linkage analysis of the pooled raw genotype data generated maximum LOD scores in the same regions as identified by GSMA. Altogether, our results have indicated that GSMA is a valuable tool to identify chromosomal regions of interest and that accumulating evidence for linkage from small peaks detected across several samples may be more important than getting a high peak in a single sample. This meta-analysis has led to identification of a novel region on chromosome 17 linked to type 2 diabetes; this region has not been highlighted in any published scan to date but on the basis of these data justifies further exploration.

Chromosome Mapping↗
PubMed2003

How well do midwives estimate the date of delivery?

OBJECTIVE: to compare expected date of delivery (EDD) and gestational age (GA) obtained by midwives with those calculated using the Confidential Enquiry into Stillbirths and Death in Infancy (CESDI) recommended formula. DESIGN: retrospective study of obstetric records and prospective study of clinical cases examined by multiple midwives. SETTING: postnatal wards, Maternity Unit, Plymouth, Devon, UK. PARTICIPANTS: two studies were performed. The first was a retrospective analysis of 115 sets of obstetric records. The second, a prospective study which included five clinical cases and 19 qualified midwives whose experience ranged from six months to 25 years. FINDINGS: in the retrospective study, 68 (59%) of the 115 obstetric case notes had sufficient information to apply the CESDI formula. The midwives'calculated EDD was interpreted to a GA and 35 (52.5%) agreed to within three days of the GA derived from the CESDI formula EDD. In the prospective study, the midwives' calculation of EDD was in good agreement with the CESDI formula in cases where last menstrual period (LMP) was known and menstrual cycle was 28 days with 17 (90%) of the 19 midwives providing the EDD to within three days of the CESDI formula. In the clinical case where LMP was known but menstrual cycle length was 33 days only two (10%) of the 19 calculated the EDD within three days of the CESDI formula. KEY CONCLUSIONS: when LMP is known and the cycle length is 28 days, midwives produce results consistent with the CESDI formula. However, when the menstrual cycle differs from 28 days or LMP is unknown, inaccurate or ambiguous and obstetric ultrasound scan (USS) information is used to calculate the EDD, the midwives show varying degrees of departure from the CESDI formula. Further, we found that the midwives tended to produce underestimates when calculating GA from EDD. This bias occurs across the range of gestations covered, including early gestations when such biases may have more important medical implications. IMPLICATIONS FOR PRACTICE: midwives' calculation of EDD and estimation of GA showed both random and systematic errors; in some cases, the errors were so large that they may have important medical consequences. If the CESDI-recommended formula for calculating EDD were used there would be improved accuracy and reliability of EDD and the calculation of GA.

Clinical Competence↗
PubMed2003

Ethnic subgroup differences in hypertension in Pakistan.

OBJECTIVE: Cardiovascular risks are globally elevated in South Asians, but this masks important ethnic subgroup differences in risk factors, such as hypertension, which have not been fully explored. We conducted this study to explore the variations in hypertension within ethnic subgroups among South Asians. DESIGN: Cross-sectional survey [National Health Survey of Pakistan (NHSP) (1990-1994)]. SETTING: Population based. PARTICIPANTS: A total of 9442 individuals aged 15 years or over. METHODS: Data on sociodemographic and clinical variables were collected. Distinct ethnic subgroups - Muhajir, Punjabi, Sindhi, Pashtun and Baluchi - were defined by mother tongue. MAIN OUTCOME MEASURE: Hypertension defined as systolic blood pressure >or= 140 mmHg or diastolic blood pressure >or= 90 mmHg, or currently receiving antihypertensive therapy. RESULTS: The age-standardized prevalence of hypertension was highest among Baluchis (25.3% in men and 41.4% in women), then Pashtuns (23.7% in men and 28.4% in women), Muhajirs (24.1% in men and 24.6% in women), and lowest among Punjabis (17.3% in men and 16.4% in women) and Sindhis (19.0% in men and 9.9% in women) (P = 0.001). While hypertension was more prevalent in urban (22.7%) versus rural dwellers (18.1%) [odds ratio (OR) 1.34; 95% confidence interval (CI), 1.20, 1.49], this difference was no longer significant after adjusting for body mass and waist circumference (OR 1.03; 95% CI, 0.91, 1.16). However, ethnic differences persisted after adjusting for major sociodemographic, dietary and clinical risk factors (unadjusted OR for Baluchi versus Sindhi, 2.92; 95% CI, 2.20-3.89; adjusted OR, 2.71; 95% CI, 1.97-3.75). CONCLUSIONS: A threefold difference in prevalence of hypertension exists between people of South Asian descent, which, unlike the urban/rural difference, cannot be accounted for by measured risk factors. Further study would provide valuable etiological and therapeutic clues.

Adolescent↗
PubMed2002

Frequent occurrence of an intron 4 mutation in multiple endocrine neoplasia type 1.

MEN1 is an autosomal dominant disorder characterized by parathyroid, pituitary, and pancreatic tumors. The MEN1 gene is located on chromosome 11q13 and encodes a 610-amino acid protein. MEN1 mutations are of diverse types and are scattered throughout the coding region, such that almost every MEN1 family will have its individual mutation. To further characterize such mutations we ascertained 34 unrelated MEN1 probands and undertook DNA sequence analysis. This identified 17 different mutations in 24 probands (2 nonsense, 2 missense, 2 in-frame deletions, 5 frameshift deletions, 1 frameshift deletional-insertion, 3 frameshift insertions, 1 donor splice site mutation, and a g-->a transition that resulted in a novel acceptor splice site in intron 4). The intron 4 mutation was found in 7 unrelated families, and the tumors in these families varied considerably, indicating a lack of genotype-phenotype correlation. However, this intron 4 mutation is the most frequently occurring germline MEN1 mutation ( approximately 10% of all mutations), and together with 5 others at codons 83-84, 118-119, 209-211, 418, and 516, accounts for 36.6% of all mutations, a finding that indicates an approach for identifying the widely diverse MEN1 mutations.

Base Sequence↗