The identification of menstrual blood in forensic samples by logistic regression modeling of miRNA expression
We report the identification of sensitive and specific miRNA biomarkers for menstrual blood, a tissue that might provide probative information in certain specialized instances. We incorporated these biomarkers into qPCR assays and developed a quantitative statistical model using logistic regression...
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| Veröffentlicht in: | Electrophoresis 2014-11, Vol.35 (21-22), p.3087-3095 |
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| container_title | Electrophoresis |
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| creator | Hanson, Erin K. Mirza, Mohid Rekab, Kamel Ballantyne, Jack |
| description | We report the identification of sensitive and specific miRNA biomarkers for menstrual blood, a tissue that might provide probative information in certain specialized instances. We incorporated these biomarkers into qPCR assays and developed a quantitative statistical model using logistic regression that permits the prediction of menstrual blood in a forensic sample with a high, and measurable, degree of accuracy. Using the developed model, we achieved 100% accuracy in determining the body fluid of interest for a set of test samples (i.e. samples not used in model development). The development, and details, of the logistic regression model are described. Testing and evaluation of the finalized logistic regression modeled assay using a small number of samples was carried out to preliminarily estimate the limit of detection (LOD), specificity in admixed samples and expression of the menstrual blood miRNA biomarkers throughout the menstrual cycle (25–28 days). The LOD was |
| doi_str_mv | 10.1002/elps.201400171 |
| format | Article |
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We incorporated these biomarkers into qPCR assays and developed a quantitative statistical model using logistic regression that permits the prediction of menstrual blood in a forensic sample with a high, and measurable, degree of accuracy. Using the developed model, we achieved 100% accuracy in determining the body fluid of interest for a set of test samples (i.e. samples not used in model development). The development, and details, of the logistic regression model are described. Testing and evaluation of the finalized logistic regression modeled assay using a small number of samples was carried out to preliminarily estimate the limit of detection (LOD), specificity in admixed samples and expression of the menstrual blood miRNA biomarkers throughout the menstrual cycle (25–28 days). 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KGaA, Weinheim.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4446-3099e9dd7464653eac1312ed89c7aa8f9371472bd16b458d0f798a78a2c492803</citedby><cites>FETCH-LOGICAL-c4446-3099e9dd7464653eac1312ed89c7aa8f9371472bd16b458d0f798a78a2c492803</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Felps.201400171$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Felps.201400171$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,777,781,1412,27905,27906,45555,45556</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25146880$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hanson, Erin K.</creatorcontrib><creatorcontrib>Mirza, Mohid</creatorcontrib><creatorcontrib>Rekab, Kamel</creatorcontrib><creatorcontrib>Ballantyne, Jack</creatorcontrib><title>The identification of menstrual blood in forensic samples by logistic regression modeling of miRNA expression</title><title>Electrophoresis</title><addtitle>ELECTROPHORESIS</addtitle><description>We report the identification of sensitive and specific miRNA biomarkers for menstrual blood, a tissue that might provide probative information in certain specialized instances. We incorporated these biomarkers into qPCR assays and developed a quantitative statistical model using logistic regression that permits the prediction of menstrual blood in a forensic sample with a high, and measurable, degree of accuracy. Using the developed model, we achieved 100% accuracy in determining the body fluid of interest for a set of test samples (i.e. samples not used in model development). The development, and details, of the logistic regression model are described. Testing and evaluation of the finalized logistic regression modeled assay using a small number of samples was carried out to preliminarily estimate the limit of detection (LOD), specificity in admixed samples and expression of the menstrual blood miRNA biomarkers throughout the menstrual cycle (25–28 days). The LOD was <1 ng of total RNA, the assay performed as expected with admixed samples and menstrual blood was identified only during the menses phase of the female reproductive cycle in two donors.</description><subject>Blood</subject><subject>Blood Chemical Analysis - methods</subject><subject>Body fluid identification</subject><subject>Body Fluids - chemistry</subject><subject>Female</subject><subject>Forensic Genetics - methods</subject><subject>Forensic science</subject><subject>Genetic Markers</subject><subject>Humans</subject><subject>Limit of Detection</subject><subject>Logistic Models</subject><subject>Logistic regression analysis</subject><subject>Logistics</subject><subject>Mathematical models</subject><subject>Menstruation</subject><subject>MicroRNA (miRNA)</subject><subject>MicroRNAs - genetics</subject><subject>Regression</subject><subject>Reproducibility of Results</subject><subject>Ribonucleic acids</subject><subject>RNA profiling</subject><subject>Samples</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><issn>0173-0835</issn><issn>1522-2683</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkTuPEzEUhS0EYsNCS4lc0kzwe-xyFe0GpCi8gra0PDN3gsEzDvZEbP49Dglp2crS8XdOcT-EXlMyp4SwdxB2ec4IFYTQmj5BMyoZq5jS_CmalYhXRHN5hV7k_IMQIowQz9EVk1QorckMDZvvgH0H4-R737rJxxHHHg8w5intXcBNiLHDfsR9TCX0Lc5u2AXIuDngELc-TyVLsE2Q87E9xA6CH7d_Z_yX9Q2Gh9358yV61ruQ4dX5vUbf7m43i_fV6uPyw-JmVbVCCFVxYgyYrquFEkpycC3llEGnTVs7p3vDaypq1nRUNULqjvS10a7WjrXCME34NXp72t2l-GsPebKDzy2E4EaI-2ypEkwxQbh8FMrKqSh9BMqFMKYcvaDzE9qmmHOC3u6SH1w6WErsUZw9irMXcaXw5ry9bwboLvg_UwUQJ-C3D3D4z5y9XX36KplSpVadasUTPFxqLv20qua1tPfrpd3Iz4v79WZpJf8DkUmy9w</recordid><startdate>201411</startdate><enddate>201411</enddate><creator>Hanson, Erin K.</creator><creator>Mirza, Mohid</creator><creator>Rekab, Kamel</creator><creator>Ballantyne, Jack</creator><general>Blackwell Publishing Ltd</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><scope>7TM</scope></search><sort><creationdate>201411</creationdate><title>The identification of menstrual blood in forensic samples by logistic regression modeling of miRNA expression</title><author>Hanson, Erin K. ; 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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Blood Blood Chemical Analysis - methods Body fluid identification Body Fluids - chemistry Female Forensic Genetics - methods Forensic science Genetic Markers Humans Limit of Detection Logistic Models Logistic regression analysis Logistics Mathematical models Menstruation MicroRNA (miRNA) MicroRNAs - genetics Regression Reproducibility of Results Ribonucleic acids RNA profiling Samples Statistical analysis Statistical methods |
| title | The identification of menstrual blood in forensic samples by logistic regression modeling of miRNA expression |
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