<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1889-836X</journal-id>
<journal-title><![CDATA[Revista de Osteoporosis y Metabolismo Mineral]]></journal-title>
<abbrev-journal-title><![CDATA[Rev Osteoporos Metab Miner]]></abbrev-journal-title>
<issn>1889-836X</issn>
<publisher>
<publisher-name><![CDATA[Sociedad Española de Investigaciones Óseas y Metabolismo Mineral]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1889-836X2023000400004</article-id>
<article-id pub-id-type="doi">10.20960/revosteoporosmetabminer.00029</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Puntuaciones de riesgo poligénico (PRS): una herramienta en la predicción de enfermedades y la medicina personalizada]]></article-title>
<article-title xml:lang="en"><![CDATA[Polygenic risk scores (PRS) &#8211; A tool for disease prediction and personalized medicine]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Real]]></surname>
<given-names><![CDATA[Álvaro del]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Riancho]]></surname>
<given-names><![CDATA[José A]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Cantabria. IDIVAL Departamento de Medicina y Psiquiatría ]]></institution>
<addr-line><![CDATA[Santander ]]></addr-line>
<country>Spain</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Cantabria. IDIVAL. CIBERER ospital Universitario Marqués de Valdecilla Servicio de Medicina Interna]]></institution>
<addr-line><![CDATA[Santander ]]></addr-line>
<country>Spain</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2023</year>
</pub-date>
<volume>15</volume>
<numero>4</numero>
<fpage>154</fpage>
<lpage>159</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_arttext&amp;pid=S1889-836X2023000400004&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_abstract&amp;pid=S1889-836X2023000400004&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_pdf&amp;pid=S1889-836X2023000400004&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En la última década, la genómica y la secuenciación de alto rendimiento han revolucionado la comprensión de las enfermedades complejas. las puntuaciones de riesgo poligénico (PRS) surgen como una prometedora herramienta para predecir enfermedades y personalizar tratamientos. Sin embargo, su implementación requiere confirmar la utilidad real y plantea importantes desafíos éticos y de privacidad. Las PRS se utilizan para identificar individuos de alto riesgo y guiar tratamientos personalizados. Su potencial es evidente en enfermedades como el cáncer o la osteoporosis, donde mejoran la estratificación de riesgo y permiten seleccionar tratamientos más efectivos. Sin embargo, las PRS tienen múltiples limitaciones, incluyendo la falta de precisión individual, la variabilidad en diferentes poblaciones y la incapacidad de considerar la influencia de los factores ambientales. La interpretación clínica y las implicaciones éticas, legales y sociales (ELSI) representan cuestiones muy relevantes en este campo. En el futuro, presumiblemente las PRS mejorarán su precisión predictiva, con la combinación de factores clínicos de riesgo y la adaptación a poblaciones de diversas etnias. Consecuentemente, se prevé que las PRS desempeñen un papel central en la medicina personalizada.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Over the past decade, genomics and high-throughput sequencing have revolutionized our understanding of complex diseases. Polygenic risk scores (PRS) have emerged as a promising tool for predicting diseases and personalizing treatments. However, their implementation requires confirmation of real utility, which raises significant ethical and privacy challenges. PRS are used to identify high-risk individuals and guide personalized treatments. Their potential is evident in diseases such as cancer or osteoporosis, where they improve risk stratification and enable the selection of more effective treatments. However, PRS have multiple limitations, including lack of individual accuracy, variability among different populations, and the inability to account for the impact of environmental factors. Clinical interpretation and ethical, legal, and social implications (ELSI) are highly relevant issues in this field. In the future, PRS are expected to improve their predictive accuracy by combining clinical risk factors and adapting to populations of various ethnicities. Consequently, PRS are expected to play a central role in personalized medicine.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Puntuaciones riesgo poligénico]]></kwd>
<kwd lng="es"><![CDATA[Medicina personalizada]]></kwd>
<kwd lng="es"><![CDATA[Estudios de asociación de genoma completo]]></kwd>
<kwd lng="en"><![CDATA[Polygenic risk scores]]></kwd>
<kwd lng="en"><![CDATA[Personalized medicine]]></kwd>
<kwd lng="en"><![CDATA[Genome-wide association studies]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>1</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[O'sullivan]]></surname>
<given-names><![CDATA[JW]]></given-names>
</name>
<name>
<surname><![CDATA[Raghavan]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Marquez-Luna]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Luzum]]></surname>
<given-names><![CDATA[JA]]></given-names>
</name>
<name>
<surname><![CDATA[Damrauer]]></surname>
<given-names><![CDATA[SM]]></given-names>
</name>
<name>
<surname><![CDATA[Ashley]]></surname>
<given-names><![CDATA[EA]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic Risk Scores for Cardiovascular Disease:A Scientific Statement from the American Heart Association]]></article-title>
<source><![CDATA[Circulation]]></source>
<year>2022</year>
<volume>146</volume>
<numero>8</numero>
<issue>8</issue>
<page-range>93-118</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Läll]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Mägi]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Morris]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Metspalu]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Fischer]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Personalized risk prediction for type 2 diabetes:the potential of genetic risk scores]]></article-title>
<source><![CDATA[Genet Med]]></source>
<year>2017</year>
<volume>19</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>322-9</page-range></nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mavaddat]]></surname>
<given-names><![CDATA[N]]></given-names>
</name>
<name>
<surname><![CDATA[Michailidou]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Dennis]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Lush]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Fachal]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes]]></article-title>
<source><![CDATA[Am J Hum Genet]]></source>
<year>2019</year>
<volume>104</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>21-34</page-range></nlm-citation>
</ref>
<ref id="B4">
<label>4</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Forgetta]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
<name>
<surname><![CDATA[Keller-Baruch]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Forest]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Durand]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Bhatnagar]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Kemp]]></surname>
<given-names><![CDATA[JP]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Development of a polygenic risk score to improve screening for fracture risk:A genetic risk prediction study]]></article-title>
<source><![CDATA[PLoS Med]]></source>
<year>2020</year>
<volume>17</volume>
<numero>7</numero>
<issue>7</issue>
</nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Khera]]></surname>
<given-names><![CDATA[AV]]></given-names>
</name>
<name>
<surname><![CDATA[Chaffin]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Aragam]]></surname>
<given-names><![CDATA[KG]]></given-names>
</name>
<name>
<surname><![CDATA[Haas]]></surname>
<given-names><![CDATA[ME]]></given-names>
</name>
<name>
<surname><![CDATA[Roselli]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Choi]]></surname>
<given-names><![CDATA[SH]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations]]></article-title>
<source><![CDATA[Nat Genet]]></source>
<year>2018</year>
<volume>50</volume>
<numero>9</numero>
<issue>9</issue>
<page-range>1219-24</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lewis]]></surname>
<given-names><![CDATA[CM]]></given-names>
</name>
<name>
<surname><![CDATA[Vassos]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic risk scores:from research tools to clinical instruments]]></article-title>
<source><![CDATA[Genome Med]]></source>
<year>2020</year>
<volume>12</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B7">
<label>7</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Choi]]></surname>
<given-names><![CDATA[SW]]></given-names>
</name>
<name>
<surname><![CDATA[Mak]]></surname>
<given-names><![CDATA[TSH]]></given-names>
</name>
<name>
<surname><![CDATA[O'Reilly]]></surname>
<given-names><![CDATA[PF]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Tutorial:a guide to performing polygenic risk score analyses]]></article-title>
<source><![CDATA[Nat Protoc]]></source>
<year>2020</year>
<volume>15</volume>
<numero>9</numero>
<issue>9</issue>
<page-range>2759-72</page-range></nlm-citation>
</ref>
<ref id="B8">
<label>8</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Collister]]></surname>
<given-names><![CDATA[JA]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[X]]></given-names>
</name>
<name>
<surname><![CDATA[Clifton]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Calculating Polygenic Risk Scores (PRS) in UK Biobank:A Practical Guide for Epidemiologists]]></article-title>
<source><![CDATA[Front Genet]]></source>
<year>2022</year>
<volume>13</volume>
</nlm-citation>
</ref>
<ref id="B9">
<label>9</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mak]]></surname>
<given-names><![CDATA[TSH]]></given-names>
</name>
<name>
<surname><![CDATA[Porsch]]></surname>
<given-names><![CDATA[RM]]></given-names>
</name>
<name>
<surname><![CDATA[Choi]]></surname>
<given-names><![CDATA[SW]]></given-names>
</name>
<name>
<surname><![CDATA[Zhou]]></surname>
<given-names><![CDATA[X]]></given-names>
</name>
<name>
<surname><![CDATA[Sham]]></surname>
<given-names><![CDATA[PC]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic scores via penalized regression on summary statistics]]></article-title>
<source><![CDATA[Genet Epidemiol]]></source>
<year>2017</year>
<volume>41</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>469-80</page-range></nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Privé]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Arbel]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Vilhjálmsson]]></surname>
<given-names><![CDATA[BJ]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[LDpred2:better, faster, stronger]]></article-title>
<source><![CDATA[Bioinformatics]]></source>
<year>2021</year>
<volume>36</volume>
<numero>22-23</numero>
<issue>22-23</issue>
<page-range>5424-31</page-range></nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wand]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Lambert]]></surname>
<given-names><![CDATA[SA]]></given-names>
</name>
<name>
<surname><![CDATA[Tamburro]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Iacocca]]></surname>
<given-names><![CDATA[MA]]></given-names>
</name>
<name>
<surname><![CDATA[O'Sullivan]]></surname>
<given-names><![CDATA[JW]]></given-names>
</name>
<name>
<surname><![CDATA[Sillari]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Improving reporting standards for polygenic scores in risk prediction studies]]></article-title>
<source><![CDATA[Nature]]></source>
<year>2021</year>
<volume>591</volume>
<numero>7849</numero>
<issue>7849</issue>
<page-range>211-9</page-range></nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mars]]></surname>
<given-names><![CDATA[N]]></given-names>
</name>
<name>
<surname><![CDATA[Koskela]]></surname>
<given-names><![CDATA[JT]]></given-names>
</name>
<name>
<surname><![CDATA[Ripatti]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Kiiskinen]]></surname>
<given-names><![CDATA[TTJ]]></given-names>
</name>
<name>
<surname><![CDATA[Havulinna]]></surname>
<given-names><![CDATA[AS]]></given-names>
</name>
<name>
<surname><![CDATA[Lindbohm]]></surname>
<given-names><![CDATA[J V]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic and clinical risk scores and their impact on age at onset and prediction of cardiometabolic diseases and common cancers]]></article-title>
<source><![CDATA[Nat Med]]></source>
<year>2020</year>
<volume>26</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>549-57</page-range></nlm-citation>
</ref>
<ref id="B13">
<label>13</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Brentnall]]></surname>
<given-names><![CDATA[AR]]></given-names>
</name>
<name>
<surname><![CDATA[Cuzick]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Buist]]></surname>
<given-names><![CDATA[DSM]]></given-names>
</name>
<name>
<surname><![CDATA[Bowles]]></surname>
<given-names><![CDATA[EJA]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Long-term Accuracy of Breast Cancer Risk Assessment Combining Classic Risk Factors and Breast Density]]></article-title>
<source><![CDATA[JAMA Oncol]]></source>
<year>2018</year>
<volume>4</volume>
<numero>9</numero>
<issue>9</issue>
</nlm-citation>
</ref>
<ref id="B14">
<label>14</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Azagra]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Roca]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Encabo]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Aguyé]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Zwart]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Güell]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[FRAX® tool, the WHO algorithm to predict osteoporotic fractures:the first analysis of its discriminative and predictive ability in the Spanish FRIDEX cohort]]></article-title>
<source><![CDATA[BMC Musculoskelet Disord]]></source>
<year>2012</year>
<volume>13</volume>
</nlm-citation>
</ref>
<ref id="B15">
<label>15</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jiang]]></surname>
<given-names><![CDATA[X]]></given-names>
</name>
<name>
<surname><![CDATA[Gruner]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Trémollieres]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Pluskiewicz]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
<name>
<surname><![CDATA[Sornay-Rendu]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Adamczyk]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Diagnostic accuracy of FRAX in predicting the 10-year risk of osteoporotic fractures using the USA treatment thresholds:A systematic review and meta-analysis]]></article-title>
<source><![CDATA[Bone]]></source>
<year>2017</year>
<volume>99</volume>
<page-range>20-5</page-range></nlm-citation>
</ref>
<ref id="B16">
<label>16</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lu]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Forgetta]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
<name>
<surname><![CDATA[Keller-Baruch]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Nethander]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Bennett]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Forest]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Improved prediction of fracture risk leveraging a genome-wide polygenic risk score]]></article-title>
<source><![CDATA[Genome Med]]></source>
<year>2021</year>
<volume>13</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>16</page-range></nlm-citation>
</ref>
<ref id="B17">
<label>17</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[del Real]]></surname>
<given-names><![CDATA[Á]]></given-names>
</name>
<name>
<surname><![CDATA[Cruz]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Olmos Martínez]]></surname>
<given-names><![CDATA[JM]]></given-names>
</name>
<name>
<surname><![CDATA[Hernández]]></surname>
<given-names><![CDATA[JL]]></given-names>
</name>
<name>
<surname><![CDATA[Valero Díaz de la Madrid]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Riancho Moral]]></surname>
<given-names><![CDATA[JA]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic risk of bone fractures in Spanish women with osteoporosis]]></article-title>
<source><![CDATA[Rev Osteoporos Metab Miner]]></source>
<year>2023</year>
<volume>15</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>66-71</page-range></nlm-citation>
</ref>
<ref id="B18">
<label>18</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rashkin]]></surname>
<given-names><![CDATA[SR]]></given-names>
</name>
<name>
<surname><![CDATA[Chua]]></surname>
<given-names><![CDATA[KC]]></given-names>
</name>
<name>
<surname><![CDATA[Ho]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Mulkey]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Jiang]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Mushiroda]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance)]]></article-title>
<source><![CDATA[Clin Pharmacol Ther]]></source>
<year>2019</year>
<volume>105</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>738-45</page-range></nlm-citation>
</ref>
<ref id="B19">
<label>19</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Johnson]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Wilke]]></surname>
<given-names><![CDATA[MAP]]></given-names>
</name>
<name>
<surname><![CDATA[Lyle]]></surname>
<given-names><![CDATA[SM]]></given-names>
</name>
<name>
<surname><![CDATA[Kowalec]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Jorgensen]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Wright]]></surname>
<given-names><![CDATA[GEB]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A Systematic Review and Analysis of the Use of Polygenic Scores in Pharmacogenomics]]></article-title>
<source><![CDATA[Clin Pharmacol Ther]]></source>
<year>2022</year>
<volume>111</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>919-30</page-range></nlm-citation>
</ref>
<ref id="B20">
<label>20</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Manousaki]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Forgetta]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
<name>
<surname><![CDATA[Keller-Baruch]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Zhao]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Greenwood]]></surname>
<given-names><![CDATA[CMT]]></given-names>
</name>
<name>
<surname><![CDATA[Mooser]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A Polygenic Risk Score as a Risk Factor for Medication-Associated Fractures]]></article-title>
<source><![CDATA[J Bone Miner Res]]></source>
<year>2020</year>
<volume>35</volume>
<numero>10</numero>
<issue>10</issue>
<page-range>1935-41</page-range></nlm-citation>
</ref>
<ref id="B21">
<label>21</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cross]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Turner]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Pirmohamed]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic risk scores:An overview from bench to bedside for personalised medicine]]></article-title>
<source><![CDATA[Front Genet]]></source>
<year>2022</year>
<volume>13</volume>
</nlm-citation>
</ref>
<ref id="B22">
<label>22</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhou]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Mori]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Ishizaki]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Takahashi]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Matsuda]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Koretsune]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Genetic risk score based on the prevalence of vertebral fracture in Japanese women with osteoporosis]]></article-title>
<source><![CDATA[Bone Reports]]></source>
<year>2016</year>
<volume>5</volume>
<page-range>168-72</page-range></nlm-citation>
</ref>
<ref id="B23">
<label>23</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gibson]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[On the utilization of polygenic risk scores for therapeutic targeting]]></article-title>
<source><![CDATA[PLoS Genet]]></source>
<year>2019</year>
<volume>15</volume>
<numero>4</numero>
<issue>4</issue>
</nlm-citation>
</ref>
<ref id="B24">
<label>24</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Herzig]]></surname>
<given-names><![CDATA[AF]]></given-names>
</name>
<name>
<surname><![CDATA[Clerget-Darpoux]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Génin]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The False Dawn of Polygenic Risk Scores for Human Disease Prediction]]></article-title>
<source><![CDATA[J Pers Med]]></source>
<year>2022</year>
<volume>12</volume>
<numero>8</numero>
<issue>8</issue>
</nlm-citation>
</ref>
<ref id="B25">
<label>25</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Roberts]]></surname>
<given-names><![CDATA[MC]]></given-names>
</name>
<name>
<surname><![CDATA[Khoury]]></surname>
<given-names><![CDATA[MJ]]></given-names>
</name>
<name>
<surname><![CDATA[Mensah]]></surname>
<given-names><![CDATA[GA]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Perspective:The Clinical Use of Polygenic Risk Scores:Race, Ethnicity, and Health Disparities]]></article-title>
<source><![CDATA[Ethn Dis]]></source>
<year>2019</year>
<volume>29</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>513-6</page-range></nlm-citation>
</ref>
<ref id="B26">
<label>26</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Evans]]></surname>
<given-names><![CDATA[DG]]></given-names>
</name>
<name>
<surname><![CDATA[van Veen]]></surname>
<given-names><![CDATA[EM]]></given-names>
</name>
<name>
<surname><![CDATA[Byers]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Roberts]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Howell]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Howell]]></surname>
<given-names><![CDATA[SJ]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The importance of ethnicity:Are breast cancer polygenic risk scores ready for women who are not of White European origin?]]></article-title>
<source><![CDATA[Int J cancer]]></source>
<year>2022</year>
<volume>150</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>73-9</page-range></nlm-citation>
</ref>
<ref id="B27">
<label>27</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Adeyemo]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Balaconis]]></surname>
<given-names><![CDATA[MK]]></given-names>
</name>
<name>
<surname><![CDATA[Darnes]]></surname>
<given-names><![CDATA[DR]]></given-names>
</name>
<name>
<surname><![CDATA[Fatumo]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Granados Moreno]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Hodonsky]]></surname>
<given-names><![CDATA[CJ]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Responsible use of polygenic risk scores in the clinic:potential benefits, risks and gaps]]></article-title>
<source><![CDATA[Nat Med]]></source>
<year>2021</year>
<volume>27</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>1876-84</page-range></nlm-citation>
</ref>
<ref id="B28">
<label>28</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lewis]]></surname>
<given-names><![CDATA[ACF]]></given-names>
</name>
<name>
<surname><![CDATA[Green]]></surname>
<given-names><![CDATA[RC]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic risk scores in the clinic:new perspectives needed on familiar ethical issues]]></article-title>
<source><![CDATA[Genome Med]]></source>
<year>2021</year>
<volume>13</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>14</page-range></nlm-citation>
</ref>
<ref id="B29">
<label>29</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wan]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Hazel]]></surname>
<given-names><![CDATA[JW]]></given-names>
</name>
<name>
<surname><![CDATA[Clayton]]></surname>
<given-names><![CDATA[EW]]></given-names>
</name>
<name>
<surname><![CDATA[Vorobeychik]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Kantarcioglu]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Malin]]></surname>
<given-names><![CDATA[BA]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Sociotechnical safeguards for genomic data privacy]]></article-title>
<source><![CDATA[Nat Rev Genet]]></source>
<year>2022</year>
<volume>23</volume>
<numero>7</numero>
<issue>7</issue>
<page-range>429-45</page-range></nlm-citation>
</ref>
<ref id="B30">
<label>30</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Khoury]]></surname>
<given-names><![CDATA[MJ]]></given-names>
</name>
<name>
<surname><![CDATA[Bowen]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Dotson]]></surname>
<given-names><![CDATA[WD]]></given-names>
</name>
<name>
<surname><![CDATA[Drzymalla]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Green]]></surname>
<given-names><![CDATA[RF]]></given-names>
</name>
<name>
<surname><![CDATA[Goldstein]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Health equity in the implementation of genomics and precision medicine:A public health imperative]]></article-title>
<source><![CDATA[Genet Med]]></source>
<year>2022</year>
<volume>24</volume>
<numero>8</numero>
<issue>8</issue>
<page-range>1630-9</page-range></nlm-citation>
</ref>
<ref id="B31">
<label>31</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Evans]]></surname>
<given-names><![CDATA[DGR]]></given-names>
</name>
<name>
<surname><![CDATA[van Veen]]></surname>
<given-names><![CDATA[EM]]></given-names>
</name>
<name>
<surname><![CDATA[Harkness]]></surname>
<given-names><![CDATA[EF]]></given-names>
</name>
<name>
<surname><![CDATA[Brentnall]]></surname>
<given-names><![CDATA[AR]]></given-names>
</name>
<name>
<surname><![CDATA[Astley]]></surname>
<given-names><![CDATA[SM]]></given-names>
</name>
<name>
<surname><![CDATA[Byers]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Breast cancer risk stratification in women of screening age:Incremental effects of adding mammographic density, polygenic risk, and a gene panel]]></article-title>
<source><![CDATA[Genet Med]]></source>
<year>2022</year>
<volume>24</volume>
<numero>7</numero>
<issue>7</issue>
<page-range>1485-94</page-range></nlm-citation>
</ref>
<ref id="B32">
<label>32</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Roberts]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Howell]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Evans]]></surname>
<given-names><![CDATA[DG]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Polygenic risk scores and breast cancer risk prediction]]></article-title>
<source><![CDATA[Breast]]></source>
<year>2023</year>
<volume>67</volume>
<page-range>71-7</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
